title: Hawkgirl

text: After the Hawkworld reboot, Hawkgirl (Hawkwoman) was now Shayera Thal and not married to Katar Hol, instead merely his police partner. In post-Hawkworld continuity, Shayera adopts the name Hawkwoman from the very beginning of her costumed career and never uses the name Hawkgirl. The Golden Age Hawkgirl is eventually returned from Limbo, but during the "" miniseries she is merged with Katar Hol and Golden Age Hawkman into a new persona.


title: Hawkgirl

text: A new Hawkgirl was introduced as part of the 1999 revival of the JSA monthly title. The new Hawkgirl is Kendra Saunders, granddaughter of the Golden Age Hawkgirl's cousin, Speed Saunders. Hawkgirl would continue to appear regularly in the monthly "JSA" series and later in the "Hawkman" monthly. In 2006, the ongoing "Hawkman" monthly series was retitled "Hawkgirl" starting with issue #50 as part of the "One Year Later" jump forward; Kendra replaced Hawkman as the lead character. The "Hawkgirl" comic book series was finished with issue #66.


title: Hawkgirl

text: The Golden Age Hawkgirl was Shiera Sanders Hall, the reincarnation of the Egyptian princess Chay-Ara, and partner of Carter Hall, the Golden Age Hawkman.


title: Hawkgirl

text: Kendra Saunders was a young Hispanic woman who took her own life. When Kendra's soul left her body, that of her grandfather's first cousin Shiera Hall, the Golden Age Hawkgirl entered it, making Kendra a walk-in. Her grandfather, former OSS agent and globe-trotting adventurer Speed Saunders, recognized this, in part due to a change in eye color, and encouraged his granddaughter to embrace her destiny as the "new" Hawkgirl.


title: Hawkgirl

text: Hawkgirl owes her powers to a belt of Nth metal, a substance native to the planet Thanagar (once home of another pair of Hawk-heroes, Katar Hol and Hawkwoman). The metal is psycho-reactive, responding to its bearer's thoughts and in its base form has a number of electromagnetic/gravitational properties. To the Hawks, it grants the power of flight, superhuman strength, super-acute vision, and an enhanced healing/regeneration ability.


title: Hawkgirl

text: Additionally, she displays advanced hand-to-hand combat skills. Like Hawkman, she retains the knowledge of several lifetimes worth of fighting. Her preferred weapons are a spear or mace, but she has also been depicted using swords, axes, warhammers, shields, and other melee weapons. She possesses shooting skills from her times as the gunfighter, Cinnamon.


title: Hawkgirl

text: In addition, the Nth metal knife which murdered Hawkgirl in her original incarnation as Chay-Ara had an unusual effect upon her soul and that of her lover Khufu (Hawkman). The pair are locked in a seemingly endless cycle of death and rebirth throughout the centuries. While not a superhuman power per se, this propensity for reincarnation has allowed Hawkgirl to cheat death and return to active duty in her current incarnation.


title: Hawkgirl

text: Like all modern Thanagarians, Shayera Hol has a pair of wings growing from her back which allows her to fly. As a Thanagarian, she has considerable physical strength, endurance and durability.


title: Hawkgirl

text: As a former member of the Thanagarian military, she had extensive training in tactics, military science, and personal combat skills. Additionally, her focus in espionage can make her a difficult opponent to track, and provides her with an advantage when tracking villains.


title: Hawkgirl

text: Hawkgirl carries a mace made of Nth metal, which can generate electric currents and repel magical energies, her mace is highly effective against magic, as shown when Hawkgirl defeated Doctor Fate, a powerful magician of the DC Universe. Hawkgirl is skilled at wielding and throwing the mace accurately. She has creatively used the mace as a shield to deflect incoming projectiles as well as a makeshift defibrillator unit.


title: Hawkgirl

text: Hawkgirl is fluent in many Earth languages, through the use of the Absorbascon. Her unique Thanagarian physiology also enables her to verbally communicate with birds.


title: Hawkgirl

text: The Nth metal also regulates the body temperature of the wearer, preventing the need for heavy protective clothing while in high altitudes. It also has the property of radiating heat, which can be controlled to warm the wearer in colder climates.


title: Hawkgirl

text: Recently, Kendra has discovered that she had enhanced healing, strength, vision and limited hover abilities when not wearing Nth metal. She speculates that this is due to her prolonged exposure to the substance. It remains to be seen if she still possesses these abilities now that she is Shiera Hall once again.


title: Hawkgirl

text: In the alternate timeline of the "Flashpoint" event, Hawkgirl joined with the Amazons' Furies. Later, Hawkgirl is seen aiding Artemis in her attempt to kill the Resistance movement member, Lois Lane. Although, Lois is rescued by Resistance member Penny Black using the smoke grenades, Penny is seriously wounded. Later, when the Furies attack Grifter and the Resistance, Hawkgirl pins Grifter down, but he pulls Hawkgirl down and then stabs her chest with a trench knife.


title: Hawkgirl

text: In the "DC Bombshells" continuity set in World War II, Shiera is a technological genius and archaeologist who aids the Bombshells with her lover, Vixen. As Hawkgirl, she uses a jetpack rather than fly with wings, though when Cheetah forces her to build weapons out of ancient technology, she designs one with wings as well as a powerful mace.


title: Hawkgirl

text: Shiera grew up in an orphanage in Mexico. From a young age she had a passion for history and ancient cultures, as well as the magnificent structures that they built. She became an archaeologist and her work caught the eye of Hans Garber. He informed her of the Zambesi Amulets and the power that they possessed.


title: Hawkgirl

text: Intrigued, Shiera went to Zambesi to try to discover the secret of the amulets. There she met Queen Mari of Zambesi and the two of them fell in love. Shiera stayed in Zambesi with Mari and became her personal mechanic, building gadgets to assist Mari against her enemies.


title: Hawkgirl

text: Hawkgirl discovered her true Thanagarian origins while fighting against Baroness Paula von Gunther. After connecting herself with an ancient mechanic god it was revealed to Shiera that her parents were members of the Wingmen of Thanagar, they sought to warn the humans of the intentions of Thanagar who wished to conquer the Earth; due to their actions they were captured and murdered.


title: Hawkgirl

text: Within the DC Super Hero Girls comics adaptation, Hawkgirl is depicted as a student at Super Hero High, being a Latina superheroine. During the issue "Hits and Myths", Kendra alongside Flash, Batgirl and Bumblebee forms a team to help Batgirl locating her missing Batplane. They track the Batplane up until a street bar. There they fight against Black Canary, Silver Banshee and Jinx, during the fight Black Canary escapes with the Batplane, so Hawkgirl, Poison Ivy, Flash, Supergirl and Batgirl chases her to retrieve the batplane, after defeating Black Canary they successfully retrieve the batplane, to celebrate their victory they all go to Themyscira with Wonder Woman to have a slumber party.


title: Hawkgirl

text: In the comic book adaptation of "", Hawkgirl (Shayera Hol) appears as a member of Superman's Regime. She first appears to answer Wonder Woman's call for heroes at the Watchtower. After being informed of the situation, the kidnapping of Superman's parents at the hands of Mirror Master, she is one of the many heroes to agree to help locate the Rogue. She battles Weather Wizard in Central City, and is later seen waiting outside the villain's bar. Hawkgirl next appears to help Wonder Woman battle the attacking Atlanteans and Aquaman. Hawkgirl battles the forces of Atlantis as Wonder Woman orders her to rescue the people who had been knocked off the boat by Aquaman's attack. She watches Arthur's forces suddenly retreat and notices the massive tsunami fast approaching. She is the first to realize there is something behind the wave. Hawkgirl spots what she believes are mountains rising out of the water, but are in fact the massive tentacles of the Kraken Aquaman called to his aid. Hawkgirl is ensnared by one of the Kraken's tentacles and dragged underwater, slowly drowning while Wonder Woman struggles to save her. After Superman arrives and forces Aquaman to call his beast off, Hawkgirl is ordered by the Man of Steel to help the sailors while Superman and the League go to give their response to Aquaman's ultimatum. Hawkgirl removes the leader of a country from his limousine during a parade before she loses him to Captain Atom. Shocked, Shiera lets her guard down and is struck by a blast of electricity, causing her to fall to the streets below. Collapsed, Hawkgirl sees Black Lightning and Huntress before the latter knocks her unconscious with an arrow bolt. Hawkgirl is later seen being held in a cell in the Batcave, glaring at Batman and Catwoman as they discuss the League's reaction to her kidnapping. When Catwoman points out the League will be searching for her, Batman disagrees and the scene cuts to the Watchtower, where to many heroes shock, a second Hawkgirl is seen arriving. The true Hawkgirl has remained trapped within the Batcave while her imposter has been revealed as the Martian Manhunter, shape-shifted into her form. Exactly a week later, the Martian Manhunter is exposed thanks to Batman's son Damian, and Bruce releases Hawkgirl as promised. Shiera makes her way to the crashed Watchtower and confirms her identity by easily putting out a lit match.


title: Hawkgirl

text: Hawkgirl goes to the Hall of Justice to question Lex Luthor over whether Sinestro truly willingly gave up his ring and powers before allowing himself to be imprisoned. Luthor confirms her questions before saying he still believes Sinestro has something else to play before Sinestro responds that the Green Lanterns will soon arrive to capture Superman and that the League will need his help to stop them. Hawkgirl is next seen waiting for Superman and Shazam in Utah at the Great Salt desert, mace at the ready as she answers Shazam's question of what the Man of Steel thinks they're dealing with by replying "He thinks we're dealing with Green Lanterns." When Superman asks how she knows, she tells him she was talking with their 'guest' at the Hall of Justice. When she sees Superman staring up into the sky, she asks how many Lanterns are on the way, with Superman replying, "Too many."


title: Hawkgirl

text: After the Green Lanterns arrive in front of them and Superman and Kilowog have a brief conversation, Shiera demands to know where Hal Jordan is, and when Kilowog doesn't respond, Superman has Cyborg fire a beam down on the Green Lanterns from the Watchtower.


title: Hawkgirl

text: The Green Lanterns survive and engage the three, with Hawkgirl fighting the Green Lanterns Isamot Kol and RRU-9-2, when she sees Superman suddenly go down, calling out his name. Shortly after, Hawkgirl is defeated, her Nth Metal mace taken by Green Lantern Tomar-Re, and her unconscious body trapped in a bubble construct alongside Shazam. Before any of them can be taken to Oa, Sinestro arrives, killing Ch'p. Shiera is freed and recovers her mace before engaging Tomar-Re and Procanon Kaa in a battle until the arrival of the Sinestro Corps. Hawkgirl flies above the captured Green Lanterns, silently observing as they remove their rings in surrender and she witnesses the Sinestro Corps depart the Earth on Sinestro's orders. During the lost seven months, Hawkgirl worked alongside fellow League members Superman and Shazam as well as Lanterns Hal, John and Sinestro in toppling more 'rogue nations' to continue establishing peace across the world.


title: Hawkgirl

text: When Hawkman returns to Thanagar and does not find Hawkgirl he goes to Earth. There he tries to force Hawkgirl to leave Superman's Regime and return home, but, loyal to Superman, Shayera fights against Hawkman; after defeating him she asks him to leave or she will kill him. Not respecting her wish, Hawkman later returns to Earth and tries to kill Superman with a kryptonite mace; he fails and is killed in a fist fight against Superman.


title: Hawkgirl

text: During their term on the Justice League John Stewart and Hawkgirl began a romance that lasted until Hawkgirl's betrayal of the Justice League. After that Stewart began something with fellow leaguer Vixen; however, during a trip to the future John Stewart met Warhawk, who called him "Dad". This baffled Stewart, but Warhawk did explain what had happen. It turned out he was the child of John and Shayera. When John returned he decided not to tell Shayera immediately; he did eventually tell her, but he also told her he would not be Destiny's puppet. Later on in the "Justice League Beyond" comic book series, it is revealed that Shayera and John get back together and gotten married after Vixen is brutally murdered by Shadow Thief. They have a son named Rex Stewart who would later join the Justice League Beyond as Warhawk. After Warhawk was born, Shayera and John decided to leave the Justice League in order to take care of Rex.


title: Hawkgirl

text: Shayera and Katar are featured in the Elseworlds three-part series "Legend of the Hawkman" (2000). The story takes place in the Earth-One timeline, some time after "The Brave and the Bold" #34. She is shown wanting to return home to Thanagar while Katar has grown accustomed to life on Earth. Although this mini-series was never labelled as an "Elseworlds" project when originally published, it is now accepted as being one, with this story clearly based on the Silver Age versions of Hawkman and Hawkgirl during the pre-"Crisis on Infinite Earths" era.


title: Hawkgirl

text: Hawkgirl (Shayera Hol) and Hawkman feature in this mini-series set soon after their arrival on Earth as the duo faces an ancient menace with connections to their Thanagarian heritage. In the first chapter, ""The Fallen One"", Shayera has been anxious to return to Thanagar, but Katar feels a responsibility to the museum, especially its upcoming extraterrestrial treasure exhibit. While Katar has adopted Earth as his home Shayera doesn't feel like they belong there. In Tibet a group of archaeologists discovers a Thanagarian gateway carved into a cliff side, after being informed of this Hawkgirl and Hawkman travel to the location.


title: Hawkgirl

text: Hawkman deciphers the writing on the gateway and it depicts the life of Thasaro, a Thanagarian child so evil that he threatened the existence of Thanagar's ancient gods. The ancient gods of Aerie condemned Thasaro into a mystic urn. Shayera's ancestor was entrusted with burying the urn so no one could release Thasaro. The archeologists and Katar want to examine the gateway but Shayera insists that the gateway be left alone. Hawkman and Shayera get into a fight until Shayera flies away heartbroken because Katar cares more about archeology than her feelings. Katar's fingerprints genetically open the gateway. Shayera hears an explosion and heads back to the site. Thasaro appears and makes the stone sentries throughout his chamber come to life. The sentries attack Hawkgirl but she manages to defeat his enforcers and finds Katar within Thasaro's grip. Thasaro then summons corpses like talons that rise up from the ground and pull Hawkgirl into a cavern beneath Thasaro's chamber. The talons maim Hawkgirl, but she manages to break away. Shayera's distress in the cavern awakens the spirit of her ancestor. Shayera's ancestor channels his aura into Shayera and gives her the edge she needs to subdue Thasaro. Thasaro is banished once again into the urn. The urn is then transported to the Midway City Museum so Katar and Shayera can safeguard it. Three months later Shayera is shown wanting to start a family, in the meantime Thanagarian zealots return to Earth to free the heinous fallen god. Thasaro's return brings chaos and devastation to Midway City, but using their Nth Metal weapons Hawkgirl and Hawkman are able to subdue him, banishing him to the fiery depths of Earth's Hell.


title: Hawkgirl

text: "Justice League Adventures" is a DC comic book series featuring the Justice League, but set in the continuity (and style) of the television shows "Justice League Animated" and "Justice League Unlimited"; as opposed to the regular DC Universe. Shayera Hol is featured in the comic, this version of Hawkgirl is really similar to the one introduced in the television show, as the comics serves as a spin-off of the series, with Hawkgirl being one of the founding members of the Justice League.


title: Hawkgirl

text: In "" and "", Hawkgirl is a member of a Justice League, and remains so even after her husband's death by Amazo, although the team faces anti-alien prejudice and suspicion. She briefly contemplates abandoning Earth when anti-alien propaganda leads to a museum exhibit dedicated to Hawkman being vandalized, but when she returns to save two children from a burning building, her faith in humanity is restored when a group of civilians stand between her and government officials attempting to bring her in as an alien, the family she saved affirming that they still see Hawkman and her as heroes. In "Another Nail", she appears to be close friends with Zatanna. She has forgiven Oliver Queen (in Amazo's body) after he admits feeling responsible for getting Katar killed, Queen believing that his attempts to prove himself caused Hawkman to put himself in danger to project the more vulnerable Oliver. Her role as the sole Hawk with League membership is much like her animated counterpart in the "Justice League" animated series.


title: Hawkgirl

text: In "", the Hawks tried to return to Thanagar to flee from Lex Luthor's military dictatorship, only to crash in the rain forests of Costa Rica. They decided to remain in hiding. They gave birth to a son and daughter, giving them natural wings. Katar and Shayera were killed in a military strike ordered by Lex Luthor, embracing each other in their final moments. The children were brought up in the jungle ever since. They were bent on revenge against Lex. As Hawkboy, the son ultimately kills Lex with Batman's permission, since he understands what he has been through.


title: Hawkgirl

text: In Alex Ross's Silver Age-toned "Justice", Hawkgirl is a member of the Justice League and co-director of the Midway City Museum, alongside her husband. With the entire JLA's secrets and weaknesses in hand, the Legion of Doom stages a simultaneous attack on nearly every member of the League. Hawkgirl and Hawkman are surprised by Toyman in the Midway City Museum, but manage to survive and decide to investigate his warehouse, where they are assaulted by his forces, and discover that he is making multiple Brainiac androids. She also appears in "Secret Origins" and "Liberty and Justice".


title: Hawkgirl

text: Hawkgirl is featured in "" comics. Much like their Silver Age counterparts, Shayera and Katar are married and very much in love.


title: Hawkgirl

text: Kendra Saunders's version of Hawkgirl is featured in "Gotham City Garage" series. She is the youngest member of a very old team. It's revealed that Kendra's parents were killed during an alien invasion, she was later rescued by the Blackhawks and trained from a young age with captain Blackhawk. She is shown using the Lady Blackhawk costume and the alias Kendra Blackhawk. She resigns from the Blackhawks in order to help the Gotham City Garage against Lex Luthor's attacks.


title: Hawkgirl

text: Hawkgirl was chosen for one of the seven features in the one-shot comic book. She lives in Chicago, working as a police detective. She is from Thanagar, her mace vibrates like a smartphone when Nth-Metal Thanagarian weapons are near and she has a secret Hawkroom. It is revealed that she did not leave Thanagar on good terms. After some time collecting Thanagarian weapons from crime scenes, she started suspecting something was wrong. This led to her fighting against an ancient Thanagarian that wanted her dead since she chose humans instead of Thanagarians.


title: Hawkgirl

text: Erica Schultz, said she was inspired by Justice League Animated version of the character, ""I've always been drawn to strong characters, but what really solidified my love for Shayera was the Justice League cartoon show.""


title: Hawkgirl

text: During a crossover with the cast of "Scooby-Doo", Silver Age version of Hawkgirl is featured alongside Hawkman in the Midway City Museum, working as curators. The heroes team-up with the characters from the animated series to discover who were stealing from their workplace. Later they uncover that Shadow Thief, Matter Master and Fadeaway Man were behind it. After a fight against the villains the heroes retrieve the stolen items.


title: Hawkgirl

text: Hawkgirl appears as Shiera Hall in the continuation series to "DC Comics Bombshells", "Bombshells: United" set in the United States in 1943. Shiera is shown in Zambesi alongside her lover, Vixen. Hawkgirl is later featured fighting against the Apokolips invasion on Earth.


title: Hawkgirl

text: IGN's list of the ""Top 25 Heroes of DC Comics"" ranked Hawkgirl as "#22". She was ranked "80th" in Comics Buyer's Guide's ""100 Sexiest Women in Comics"" list.


title: The Gray Man (2007 film)

text: The Gray Man (previously known as Wysteria: The Horrible Story of Albert Fish) is a 2007 biographical thriller film based on the actual life and events of American serial killer, rapist and cannibal Albert Fish. It premiered at the Montreal World Film Festival on August 31, 2007, and was scheduled for a theatrical release sometime in 2007. It is directed by Scott Flynn and stars Belgian actor Patrick Bauchau as Albert Fish.


title: The Gray Man (2007 film)

text: At St. John's Orphanage in 1877, children, including a young Albert Fish, are being paddled as punishment for their sins. Albert Fish as an adult (Patrick Bauchau) then tells of a horse that some older boys at the orphanage set on fire, comparing himself to the horse. He regularly whips himself with a belt while hallucinating himself as he appeared in the orphanage. Fish kills a boy scout, Francis McDonnell, before visiting the Budd family home, where he abducts and murders ten-year-old Grace Budd (Lexi Ainsworth) on June 3, 1928, under the pretense of taking her to his niece's birthday party. Throughout the film is a film noir-style narration by Detective William King (Jack Conley), of the Missing Persons Bureau. King searches for Grace Budd for six years, before finally tracking down and arresting Fish. Fish is found guilty despite evidence of his insanity, and promptly sentenced to die.


title: The Gray Man (2007 film)

text: "Variety"s Dennis Harvey wrote, "A chilling turn by Patrick Bauchau as Albert Fish, the seemingly harmless old gent exposed in 1934 as a serial child murderer, dominates "The Gray Man". Skirting graphic horror terrain for a less sensational character study/detective-procedural, helmer Scott Flynn's debut feature manages to be just moderately compelling despite the grotesque subject. Cable and DVD sales are signaled."


title: Sentiment analysis

text: Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, also more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.


title: Sentiment analysis

text: A basic task in sentiment analysis is classifying the "polarity" of a given text at the document, sentence, or feature/aspect level—whether the expressed opinion in a document, a sentence or an entity feature/aspect is positive, negative, or neutral. Advanced, "beyond polarity" sentiment classification looks, for instance, at emotional states such as enjoyment, anger, disgust, sadness, fear, and surprise.


title: Sentiment analysis

text: Precursors to sentimental analysis include the General Inquirer, which provided hints toward quantifying patterns in text and, separately, psychological research that examined a person's psychological state based on analysis of their verbal behavior.


title: Sentiment analysis

text: Subsequently, the method described in a patent by Volcani and Fogel, looked specifically at sentiment and identified individual words and phrases in text with respect to different emotional scales. A current system based on their work, called EffectCheck, presents synonyms that can be used to increase or decrease the level of evoked emotion in each scale.


title: Sentiment analysis

text: Many other subsequent efforts were less sophisticated, using a mere polar view of sentiment, from positive to negative, such as work by Turney, and Pang who applied different methods for detecting the polarity of product reviews and movie reviews respectively. This work is at the document level. One can also classify a document's polarity on a multi-way scale, which was attempted by Pang and Snyder among others: Pang and Lee expanded the basic task of classifying a movie review as either positive or negative to predict star ratings on either a 3- or a 4-star scale, while Snyder performed an in-depth analysis of restaurant reviews, predicting ratings for various aspects of the given restaurant, such as the food and atmosphere (on a five-star scale).


title: Sentiment analysis

text: First steps to bringing together various approaches—learning, lexical, knowledge-based, etc.—were taken in the 2004 AAAI Spring Symposium where linguists, computer scientists, and other interested researchers first aligned interests and proposed shared tasks and benchmark data sets for the systematic computational research on affect, appeal, subjectivity, and sentiment in text.


title: Sentiment analysis

text: Even though in most statistical classification methods, the neutral class is ignored under the assumption that neutral texts lie near the boundary of the binary classifier, several researchers suggest that, as in every polarity problem, three categories must be identified. Moreover, it can be proven that specific classifiers such as the Max Entropy and SVMs can benefit from the introduction of a neutral class and improve the overall accuracy of the classification. There are in principle two ways for operating with a neutral class. Either, the algorithm proceeds by first identifying the neutral language, filtering it out and then assessing the rest in terms of positive and negative sentiments, or it builds a three-way classification in one step. This second approach often involves estimating a probability distribution over all categories (e.g. naive Bayes classifiers as implemented by the NLTK). Whether and how to use a neutral class depends on the nature of the data: if the data is clearly clustered into neutral, negative and positive language, it makes sense to filter the neutral language out and focus on the polarity between positive and negative sentiments. If, in contrast, the data are mostly neutral with small deviations towards positive and negative affect, this strategy would make it harder to clearly distinguish between the two poles.


title: Sentiment analysis

text: A different method for determining sentiment is the use of a scaling system whereby words commonly associated with having a negative, neutral, or positive sentiment with them are given an associated number on a −10 to +10 scale (most negative up to most positive) or simply from 0 to a positive upper limit such as +4. This makes it possible to adjust the sentiment of a given term relative to its environment (usually on the level of the sentence). When a piece of unstructured text is analyzed using natural language processing, each concept in the specified environment is given a score based on the way sentiment words relate to the concept and its associated score. This allows movement to a more sophisticated understanding of sentiment, because it is now possible to adjust the sentiment value of a concept relative to modifications that may surround it. Words, for example, that intensify, relax or negate the sentiment expressed by the concept can affect its score. Alternatively, texts can be given a positive and negative sentiment strength score if the goal is to determine the sentiment in a text rather than the overall polarity and strength of the text.


title: Sentiment analysis

text: There are various other types of sentiment analysis like- Aspect Based sentiment analysis, Grading sentiment analysis (positive, negative, neutral), Multilingual sentiment analysis and detection of emotions.


title: Sentiment analysis

text: This task is commonly defined as classifying a given text (usually a sentence) into one of two classes: objective or subjective. This problem can sometimes be more difficult than polarity classification. The subjectivity of words and phrases may depend on their context and an objective document may contain subjective sentences (e.g., a news article quoting people's opinions). Moreover, as mentioned by Su, results are largely dependent on the definition of subjectivity used when annotating texts. However, Pang showed that removing objective sentences from a document before classifying its polarity helped improve performance.


title: Sentiment analysis

text: The term subjective describes the incident contains non-factual information in various forms, such as personal opinions, judgment, and predictions. Also known as 'private states' mentioned by Quirk et al. In the example down below, it reflects a private states 'We Americans'.  Moreover, the target entity commented by the opinions can take several forms from tangible product to intangible topic matters stated in Liu(2010). Furthermore, three types of attitudes were observed by Liu(2010), 1) positive opinions, 2) neutral opinions, and 3) negative opinions.


title: Sentiment analysis

text: Each class's collections of words or phrase indicators are defined for to locate desirable patterns on unannotated text. For subjective expression, a different word list has been created. Lists of subjective indicators in words or phrases have been developed by multiple researchers in the linguist and natural language processing field states in Riloff et al.(2003). A dictionary of extraction rules has to be created for measuring given expressions. Over the years, in subjective detection, the features extraction progression from curating features by hand to automated features learning. At the moment, automated learning methods can further separate into supervised and unsupervised machine learning. Patterns extraction with machine learning process annotated and unannotated text have been explored extensively by academic researchers.


title: Sentiment analysis

text: However, researchers recognized several challenges in developing fixed sets of rules for expressions respectably. Much of the challenges in rule development stems from the nature of textual information. Six challenges have been recognized by several researchers: 1) metaphorical expressions, 2) discrepancies in writings, 3) context-sensitive, 4) represented words with fewer usages, 5) time-sensitive, and 6) ever-growing volume.


title: Sentiment analysis

text: Previously, the research mainly focused on document level classification. However, classifying a document level suffers less accuracy, as an article may have diverse types of expressions involved. Researching evidence suggests a set of news articles that are expected to dominate by the objective expression, whereas the results show that it consisted of over 40% of subjective expression.


title: Sentiment analysis

text: To overcome those challenges, researchers conclude that classifier efficacy depends on the precisions of patterns learner. And the learner feeds with large volumes of annotated training data outperformed those trained on less comprehensive subjective features. However, one of the main obstacles to executing this type of work is to generate a big dataset of annotated sentences manually. The manual annotation method has been less favored than automatic learning for three reasons:


title: Sentiment analysis

text: All these mentioned reasons can impact on the efficiency and effectiveness of subjective and objective classification. Accordingly, two bootstrapping methods were designed to learning linguistic patterns from unannotated text data. Both methods are starting with a handful of seed words and unannotated textual data.


title: Sentiment analysis

text: Overall, these algorithms highlight the need for automatic pattern recognition and extraction in subjective and objective task.


title: Sentiment analysis

text: Subjective and object classifier can enhance the serval applications of natural language processing. One of the classifier's primary benefits is that it popularized the practice of data-driven decision-making processes in various industries.  According to Liu, the applications of subjective and objective identification have been implemented in business, advertising, sports, and social science.


title: Sentiment analysis

text: It refers to determining the opinions or sentiments expressed on different features or aspects of entities, e.g., of a cell phone, a digital camera, or a bank. A feature or aspect is an attribute or component of an entity, e.g., the screen of a cell phone, the service for a restaurant, or the picture quality of a camera. The advantage of feature-based sentiment analysis is the possibility to capture nuances about objects of interest. Different features can generate different sentiment responses, for example a hotel can have a convenient location, but mediocre food. This problem involves several sub-problems, e.g., identifying relevant entities, extracting their features/aspects, and determining whether an opinion expressed on each feature/aspect is positive, negative or neutral. The automatic identification of features can be performed with syntactic methods, with topic modeling, or with deep learning. More detailed discussions about this level of sentiment analysis can be found in Liu's work.


title: Sentiment analysis

text: Emotions and sentiments are subjective in nature. The degree of emotions/sentiments expressed in a given text at the document, sentence, or feature/aspect level—to what degree of intensity is expressed in the opinion of a document, a sentence or an entity differs on a case-to-case basis. However, predicting only the emotion and sentiment does not always convey complete information. The degree or level of emotions and sentiments often plays a crucial role in understanding the exact feeling within a single class (e.g., 'good' versus 'awesome'). Some methods leverage a stacked ensemble method for predicting intensity for emotion and sentiment by combining the outputs obtained and using deep learning models based on convolutional neural networks, long short-term memory networks and gated recurrent units.


title: Sentiment analysis

text: Existing approaches to sentiment analysis can be grouped into three main categories: knowledge-based techniques, statistical methods, and hybrid approaches. Knowledge-based techniques classify text by affect categories based on the presence of unambiguous affect words such as happy, sad, afraid, and bored. Some knowledge bases not only list obvious affect words, but also assign arbitrary words a probable "affinity" to particular emotions. Statistical methods leverage elements from machine learning such as latent semantic analysis, support vector machines, "bag of words", "Pointwise Mutual Information" for Semantic Orientation, semantic space models or word embedding models, and deep learning. More sophisticated methods try to detect the holder of a sentiment (i.e., the person who maintains that affective state) and the target (i.e., the entity about which the affect is felt). To mine the opinion in context and get the feature about which the speaker has opined, the grammatical relationships of words are used. Grammatical dependency relations are obtained by deep parsing of the text. Hybrid approaches leverage both machine learning and elements from knowledge representation such as ontologies and semantic networks in order to detect semantics that are expressed in a subtle manner, e.g., through the analysis of concepts that do not explicitly convey relevant information, but which are implicitly linked to other concepts that do so.


title: Sentiment analysis

text: Open source software tools as well as range of free and paid sentiment analysis tools deploy machine learning, statistics, and natural language processing techniques to automate sentiment analysis on large collections of texts, including web pages, online news, internet discussion groups, online reviews, web blogs, and social media. Knowledge-based systems, on the other hand, make use of publicly available resources, to extract the semantic and affective information associated with natural language concepts. The system can help perform affective commonsense reasoning. Sentiment analysis can also be performed on visual content, i.e., images and videos (see Multimodal sentiment analysis). One of the first approaches in this direction is SentiBank utilizing an adjective noun pair representation of visual content. In addition, the vast majority of sentiment classification approaches rely on the bag-of-words model, which disregards context, grammar and even word order. Approaches that analyses the sentiment based on how words compose the meaning of longer phrases have shown better result, but they incur an additional annotation overhead.


title: Sentiment analysis

text: A human analysis component is required in sentiment analysis, as automated systems are not able to analyze historical tendencies of the individual commenter, or the platform and are often classified incorrectly in their expressed sentiment. Automation impacts approximately 23% of comments that are correctly classified by humans. However, humans often disagree, and it is argued that the inter-human agreement provides an upper bound that automated sentiment classifiers can eventually reach.


title: Sentiment analysis

text: The accuracy of a sentiment analysis system is, in principle, how well it agrees with human judgments. This is usually measured by variant measures based on precision and recall over the two target categories of negative and positive texts. However, according to research human raters typically only agree about 80% of the time (see Inter-rater reliability). Thus, a program that achieves 70% accuracy in classifying sentiment is doing nearly as well as humans, even though such accuracy may not sound impressive. If a program were "right" 100% of the time, humans would still disagree with it about 20% of the time, since they disagree that much about "any" answer.


title: Sentiment analysis

text: On the other hand, computer systems will make very different errors than human assessors, and thus the figures are not entirely comparable. For instance, a computer system will have trouble with negations, exaggerations, jokes, or sarcasm, which typically are easy to handle for a human reader: some errors a computer system makes will seem overly naive to a human. In general, the utility for practical commercial tasks of sentiment analysis as it is defined in academic research has been called into question, mostly since the simple one-dimensional model of sentiment from negative to positive yields rather little actionable information for a client worrying about the effect of public discourse on e.g. brand or corporate reputation.


title: Sentiment analysis

text: To better fit market needs, evaluation of sentiment analysis has moved to more task-based measures, formulated together with representatives from PR agencies and market research professionals. The focus in e.g. the RepLab evaluation data set is less on the content of the text under consideration and more on the effect of the text in question on brand reputation.


title: Sentiment analysis

text: Because evaluation of sentiment analysis is becoming more and more task based, each implementation needs a separate training model to get a more accurate representation of sentiment for a given data set.


title: Sentiment analysis

text: The rise of social media such as blogs and social networks has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations. As businesses look to automate the process of filtering out the noise, understanding the conversations, identifying the relevant content and actioning it appropriately, many are now looking to the field of sentiment analysis. Further complicating the matter, is the rise of anonymous social media platforms such as 4chan and Reddit. If web 2.0 was all about democratizing publishing, then the next stage of the web may well be based on democratizing data mining of all the content that is getting published.


title: Sentiment analysis

text: One step towards this aim is accomplished in research. Several research teams in universities around the world currently focus on understanding the dynamics of sentiment in e-communities through sentiment analysis. The CyberEmotions project, for instance, recently identified the role of negative emotions in driving social networks discussions.


title: Sentiment analysis

text: The problem is that most sentiment analysis algorithms use simple terms to express sentiment about a product or service. However, cultural factors, linguistic nuances, and differing contexts make it extremely difficult to turn a string of written text into a simple pro or con sentiment. The fact that humans often disagree on the sentiment of text illustrates how big a task it is for computers to get this right. The shorter the string of text, the harder it becomes.


title: Sentiment analysis

text: Even though short text strings might be a problem, sentiment analysis within microblogging has shown that Twitter can be seen as a valid online indicator of political sentiment. Tweets' political sentiment demonstrates close correspondence to parties' and politicians' political positions, indicating that the content of Twitter messages plausibly reflects the offline political landscape. Furthermore, sentiment analysis on Twitter has also been shown to capture the public mood behind human reproduction cycles globally, as well as other problems of public-health relevance such as adverse drug reactions.


title: Sentiment analysis

text: While sentiment analysis has been popular for domains where authors express their opinion rather explicitly ("the movie is awesome"), such as social media and product reviews, only recently robust methods were devised for other domains where sentiment is strongly implicit or indirect. For example, in news articles - mostly due to the expected journalistic objectivity - journalists often describe actions or events rather than directly stating the polarity of a piece of information. Earlier approaches using dictionaries or shallow machine learning features were unable to catch the "meaning between the lines", but recently researchers have proposed a deep learning based approach and dataset that is able to analyze sentiment in news articles.


title: Sentiment analysis

text: For a recommender system, sentiment analysis has been proven to be a valuable technique. A recommender system aims to predict the preference for an item of a target user. Mainstream recommender systems work on explicit data set. For example, collaborative filtering works on the rating matrix, and content-based filtering works on the meta-data of the items.


title: Sentiment analysis

text: In many social networking services or e-commerce websites, users can provide text review, comment or feedback to the items. These user-generated text provide a rich source of user's sentiment opinions about numerous products and items. Potentially, for an item, such text can reveal both the related feature/aspects of the item and the users' sentiments on each feature. The item's feature/aspects described in the text play the same role with the meta-data in content-based filtering, but the former are more valuable for the recommender system. Since these features are broadly mentioned by users in their reviews, they can be seen as the most crucial features that can significantly influence the user's experience on the item, while the meta-data of the item (usually provided by the producers instead of consumers) may ignore features that are concerned by the users. For different items with common features, a user may give different sentiments. Also, a feature of the same item may receive different sentiments from different users. Users' sentiments on the features can be regarded as a multi-dimensional rating score, reflecting their preference on the items.


title: Sentiment analysis

text: Based on the feature/aspects and the sentiments extracted from the user-generated text, a hybrid recommender system can be constructed. There are two types of motivation to recommend a candidate item to a user. The first motivation is the candidate item have numerous common features with the user's preferred items, while the second motivation is that the candidate item receives a high sentiment on its features. For a preferred item, it is reasonable to believe that items with the same features will have a similar function or utility. So, these items will also likely to be preferred by the user. On the other hand, for a shared feature of two candidate items, other users may give positive sentiment to one of them while giving negative sentiment to another. Clearly, the high evaluated item should be recommended to the user. Based on these two motivations, a combination ranking score of similarity and sentiment rating can be constructed for each candidate item.


title: Sentiment analysis

text: Except for the difficulty of the sentiment analysis itself, applying sentiment analysis on reviews or feedback also faces the challenge of spam and biased reviews. One direction of work is focused on evaluating the helpfulness of each review. Review or feedback poorly written is hardly helpful for recommender system. Besides, a review can be designed to hinder sales of a target product, thus be harmful to the recommender system even it is well written.


title: Sentiment analysis

text: Researchers also found that long and short forms of user-generated text should be treated differently. An interesting result shows that short-form reviews are sometimes more helpful than long-form, because it is easier to filter out the noise in a short-form text. For the long-form text, the growing length of the text does not always bring a proportionate increase in the number of features or sentiments in the text.


title: Sentiment analysis

text: Lamba & Madhusudhan introduce a nascent way to cater the information needs of today's library users by repackaging the results from sentiment analysis of social media platforms like Twitter and provide it as a consolidated time-based service in different formats. Further, they propose a new way of conducting marketing in libraries using social media mining and sentiment analysis.


title: Daisy Buchanan

text: Daisy Fay Buchanan is a fictional character in F. Scott Fitzgerald's 1925 novel "The Great Gatsby". The character is a wealthy socialite from Louisville, Kentucky who resides in the fashionable town of East Egg on Long Island during the Jazz Age. She is narrator Nick Carraway's second cousin, once removed, and the wife of polo player Tom Buchanan, by whom she has a daughter. Before marrying Tom, Daisy had a romantic relationship with Jay Gatsby. Her choice between Gatsby and Tom is one of the novel's central conflicts. Described by Fitzgerald as a "golden girl", she is the target of both Tom's callous domination and Gatsby's dehumanizing adoration. The ensuing contest of wills between Tom and Gatsby reduces Daisy to a trophy wife whose sole existence is to augment her possessor's socio-economic success.


title: Daisy Buchanan

text: Fitzgerald based the fictional character on socialite Ginevra King. Fitzgerald and King shared a passionate romance from 1915 to 1917, but their relationship stagnated after King's father purportedly warned the writer that "poor boys shouldn't think of marrying rich girls". After their relationship ended, a distraught Fitzgerald dropped out of Princeton University and enlisted in the United States Army amid World War I, while King entered into an arranged marriage with William "Bill" Mitchell, a polo player who partly served as the model for Tom Buchanan. Following King's separation from Mitchell in 1937, Fitzgerald attempted to reunite with King when she visited Hollywood in 1938. The reunion proved a disaster due to Fitzgerald's alcoholism. Scholar Maureen Corrigan notes that "because she's the one who got away, Ginevra—even more than [his wife] Zelda—is the love who lodged like an irritant in Fitzgerald's imagination, producing the literary pearl that is Daisy Buchanan".


title: Daisy Buchanan

text: The character of Daisy Buchanan has been identified as personifying the cultural archetype of the flapper. Flappers were typically young, modern women who bobbed their hair and wore short skirts. They also drank alcohol and had premarital sex. Despite the newfound societal freedoms attained by flappers in the 1920s, Fitzgerald's novel examines the continued limitations upon women's agency during this period. In this context, although early critics viewed the character of Daisy to be a "monster of bitchery", later scholars assert that Daisy's character exemplifies the marginalization of women in the elite social milieu that Fitzgerald depicts.


title: Daisy Buchanan

text: The character has appeared in various media related to the novel, including stage plays, radio shows, television episodes, and feature films. New York actress Florence Eldridge originated the role of Daisy on the stage when she starred in the 1926 Broadway adaptation of Fitzgerald's novel at the Ambassador Theatre in New York City. That same year, screen actress Lois Wilson played the role in the now lost 1926 silent film adaptation. During the subsequent decades, the role has been played by many actresses including Betty Field, Phyllis Kirk, Jeanne Crain, Mia Farrow, Mira Sorvino, Pippa Bennett-Warner, Carey Mulligan, and others.


title: Daisy Buchanan

text: Daisy Fay was raised in luxury in Louisville, Kentucky, during the Jim Crow period. In 1917, although she had several suitors belonging to her same privileged social class, she entered into a month-long relationship with impoverished doughboy Jay Gatsby which ended with them promising to marry each other in the future. While Gatsby served in World War I, Daisy married polo player Thomas "Tom" Buchanan. The couple moved to East Egg, an "old money" enclave on Long Island, where they resided in a cheerful red-and-white Georgian Colonial mansion overlooking Manhasset Bay.


title: Daisy Buchanan

text: After her cousin Nick Carraway arrived at the neighboring ""nouveau riche"" town of West Egg, he met Gatsby, who had become a millionaire. Gatsby had moved to Long Island in order to reunite with Daisy, and he threw extravagant soirées at his mansion, hoping she might attend. Nick arranged a "" between Daisy and Jay at his cottage in West Egg. The two met for the first time in five years and began a sexual affair.


title: Daisy Buchanan

text: Later at the Buchanan residence, Daisy, Tom, and Gatsby—as well as her friends Nick and Jordan Baker—decided to visit the twenty-story Plaza Hotel, a château-like edifice in New York City with an architectural style inspired by the French Renaissance. Tom embarked in Gatsby's yellow Rolls Royce with Jordan and Nick, while Daisy and Gatsby drove alone in Tom's blue coupé. After the ensemble reached the hotel, a confrontation ensued between Tom and Gatsby regarding Daisy's infidelity. Though Gatsby insisted that Daisy never loved Tom, Daisy admitted that she loved both Tom and Gatsby. The confrontation ended with Daisy leaving with Gatsby in his yellow car, while Tom departed with Nick and Jordan.


title: Daisy Buchanan

text: Tom's mistress Myrtle Wilson had previously seen Tom driving Gatsby's yellow car in the "valley of ashes", a sprawling refuse dump. When she saw it approach that evening on its way back to East Egg, she ran in front of Gatsby's car in hopes of reconciling with Tom. Daisy ran her over. Gatsby stopped the car by applying the emergency brake and then took over driving from Daisy, fleeing the scene of the accident.


title: Daisy Buchanan

text: At her home in East Egg, Gatsby assured Daisy that he would take the blame for Myrtle's death. Tom informed Myrtle's husband George Wilson that it was Gatsby who killed Myrtle. A distraught George traveled to Gatsby's mansion in West Egg and shot Gatsby dead before turning the weapon on himself. Soon after Gatsby's murder, Daisy, Tom, and their daughter departed East Egg, leaving no forwarding address.


title: Daisy Buchanan

text: Fitzgerald based the character of Daisy Buchanan on Chicago socialite and heiress Ginevra King, whom he met on a visit back home in St. Paul, Minnesota, while enrolled as a student at Princeton University. The 18-year-old aspiring writer fell deeply in love with the 16-year-old King, and he wrote to her "daily the incoherent, expressive letters all young lovers write". In Fitzgerald's mind, Ginerva became the "archetype for the alluring, independent and upper-class woman, ultimately unattainable by someone of a modest social background like himself". Even after his later marriage to Zelda Sayre, Fitzgerald continued to view King as an unobtainable ideal who embodied the elusive American dream. According to acquaintances, "Fitzgerald was so smitten by King that for years he could not think of her without tears coming to his eyes".


title: Daisy Buchanan

text: During their two relationship, Ginevra wrote a Gatsby-like short story that she sent to Fitzgerald. In her story, she is trapped in a loveless marriage with a wealthy man yet still pines for Fitzgerald, a former lover from her past. The lovers are reunited only after Fitzgerald has attained enough money to take her away from her adulterous husband. Fitzgerald kept Ginevra's story with him until his death, and scholars have noted the plot similarities between Ginevra's story and Fitzgerald's novel "The Great Gatsby". King would greatly influence Fitzgerald's writing, far more so than his wife Zelda Sayre. Scholar Maureen Corrigan notes that "because she's the one who got away, Ginevra—even more than Zelda—is the love who lodged like an irritant in Fitzgerald's imagination, producing the literary pearl that is Daisy Buchanan".


title: Daisy Buchanan

text: In August 1916, Fitzgerald visited Ginevra at her family's villa in the upper-class enclave of Lake Forest, Illinois. At the time, Lake Forest "was off-limits to Black and Jewish people," and the recurrent appearance of a middle-class Irish Catholic parvenu such as Fitzgerald in the exclusively White Anglo-Saxon Protestant area would have caused a stir. A conspicuously out-of-place Fitzgerald was purportedly told by Ginevra's imperious father, stockbroker Charles Garfield King, that "poor boys shouldn't think of marrying rich girls". After their relationship ended in January 1917, a distraught Fitzgerald dropped out of Princeton University and enlisted in the United States Army amid World War I, while King abruptly entered into an arranged marriage with her first husband, William "Bill" Mitchell, an avid polo player who partly served as the model for Thomas "Tom" Buchanan in the same novel. Mitchell would become a director of Texaco, one of the most successful oil companies of the era.


title: Daisy Buchanan

text: King separated from Mitchell in 1937 after an unhappy marriage. One year later, Fitzgerald attempted to reunite with King when she visited Hollywood in 1938. The reunion proved a disaster due to Fitzgerald's alcoholism, and a disappointed King returned to Chicago. Her second husband, John T. Pirie Jr., was a business tycoon and owner of the Chicago department retailer Carson Pirie Scott & Company. Reflecting in her later years upon her romance with Fitzgerald, King remarked: "Goodness, what a self-centered little ass I was!" She died in 1980 at the age of 82 at her family's estate in Charleston, South Carolina.


title: Daisy Buchanan

text: To a lesser extent, Fitzgerald partially based Daisy on his wife Zelda. Writer Therese Anne Fowler has noted several similarities that both Daisy and Zelda shared: "the Southern upbringing, the prominent family." According to Zelda's biographer Nancy Milford, "if there was a Confederate establishment in the Deep South, Zelda Sayre came from the heart of it". Zelda Sayre was the granddaughter of Confederate Senator Willis B. Machen. Her father's uncle was John Tyler Morgan, a Confederate general in the American Civil War and the second Grand Dragon of the Ku Klux Klan in Alabama. In addition to their leadership of the Alabama Ku Klux Klan, Zelda's family owned the White House of the Confederacy.


title: Daisy Buchanan

text: During her idle youth, Zelda Sayre's wealthy Southern family employed half-a-dozen domestic servants, many of whom were African-American. Consequently, much like Daisy Buchanan, Zelda was unaccustomed to domestic labor or responsibilities of any kind. When their daughter Scottie was born, Fitzgerald recorded Zelda saying as she emerged from the anesthesia: "Oh, God... I'm drunk. Mark Twain. Isn't she smart—she has the hiccups. I hope it's beautiful and a fool—a beautiful little fool." Fitzgerald partly used this quotation for Daisy's dialogue in "The Great Gatsby".


title: Daisy Buchanan

text: The character of Daisy Buchanan has been identified specifically as personifying the Jazz Age archetype of the flapper. Flappers were typically young, modern women who bobbed their hair and wore short skirts. They also drank alcohol and had premarital sex. Despite the newfound societal freedoms attained by flappers in the 1920s, Fitzgerald's work critically examines the continued limitations upon women's agency during this period. In this context, although early critics viewed the character of Daisy to be a "monster of bitchery", later scholars asserted that the character exemplifies the marginalization of women in the elite social milieu that Fitzgerald depicts.


title: Daisy Buchanan

text: In the 1940s and 1950s, many scholars and critics unequivocally condemned Daisy as an irredeemable villain. Critic Marius Bewley remarked upon the character's "vicious emptiness," Robert Ornstein dubbed her "criminally immoral," Alfred Kazin judged her to be "vulgar and inhuman," and Leslie Fiedler regarded her as a "dark destroyer" who purveys "corruption and death". In these earlier critiques, Gatsby was likened unto an innocent and Daisy equated with "foul dust [that] floated in the wake of his dreams".


title: Daisy Buchanan

text: Revisionist opinions about the character began to emerge over time in the 1960s and 1970s. Writing in 1978, scholar Leland S. Person noted Daisy is more of a hapless victim than a manipulative victimizer. Described by Fitzgerald as a "golden girl", she is the target first of Tom's callous domination and next of Gatsby's dehumanizing adoration. She involuntarily becomes the holy grail at the center of Gatsby's unrealistic quest to be steadfast to a youthful concept of himself. The ensuing contest of wills between Tom and Gatsby reduces Daisy to a trophy wife whose sole existence is to augment her possessor's socio-economic success.


title: Daisy Buchanan

text: As an upper-class white woman living in East Egg during this time period, Daisy must adhere to societal expectations and gender norms such as actively fulfilling the roles of dutiful wife, nurturing mother, and charming socialite. Many of Daisy's choices—ultimately culminating in the fatal car crash and misery for all those involved—can be partly attributed to her prescribed role as a "beautiful little fool" who is reliant on her husband for financial and societal security. Her decision to remain with her husband, despite her feelings for Gatsby, is because of the security that her marriage to Tom Buchanan provides.


title: Daisy Buchanan

text: Notwithstanding this scholarly reevaluation in academia, many contemporary readers continue to regard Daisy as an antagonist or an antiheroine. Often listed as among "the most discussed and polarizing female characters in American literature," readers frequently vilify Daisy for the consequences of her actions, such as directly and indirectly causing the deaths of several characters. Writer Ester Bloom has opined that, although Daisy is not technically the story's villain, "she still sucks, and if it weren't for her, a couple of key players in the book would be alive at the end of it."


title: Daisy Buchanan

text: Despite such widespread antipathy, many readers have sympathized with the character. Writer Katie Baker observed that, although Daisy lives and Gatsby dies, "in the end, both Gatsby and Daisy have lost their youthful dreams, that sense of eternal possibility that made the summertimes sweet. And love her or hate her, there's something to pity in that irrevocable fact." Dave McGinn listed the character as one who needed their side of the story told. He questioned if she truly had a "voice full of money", as Gatsby claimed, and wondered what her thoughts were on the love triangle between her, Gatsby and Tom.


title: Daisy Buchanan

text: Both Daisy Buchanan and her husband Tom are often invoked in popular discourse in the context of careless indifference by affluent persons. In July 2016, on the eve of the 2016 United States presidential election, "New York Times" columnist Maureen Dowd likened Hillary Clinton and Bill Clinton to Daisy and Tom Buchanan due to their perceived carelessness in the political arena. Dowd wrote: "And that's the corkscrew way things go with the Clintons, who are staying true to their reputation as the Tom and Daisy Buchanan of American politics. Their vast carelessness drags down everyone around them, but they persevere, and even thrive." Four years later, in October 2020, the response of Donald Trump's administration to the COVID-19 pandemic was compared by "New York Times" writer Ian Prasad Philbrick to the careless indifference of Daisy and Tom Buchanan. The "blasé Buchanans in the novel's final pages," Philbrick remarked, "seemed to fit an administration that has attempted to downplay the pandemic, even after Trump and other top Republicans tested positive for Covid-19."


title: Daisy Buchanan

text: Daisy has been cited as a role model for young women who aspire to attain wealth and to live life for the moment. "You should take Daisy's advice: be a 'fool'," urged writer Carlie Lindower of Mic.com, "Be a fool and covet only what is on the surface—the pearls, the furs, the immaculate lawn—because any deeper than that is murky territory filled with misguided ideals and broken pillars of feminism." Similarly, Inga Ting of "The Sydney Morning Herald" posited that Daisy's materialistic ambitions are both understandable and rationale as indicated by peer-reviewed academic studies. "Men want beauty," Ting opined, "women want money".


title: Daisy Buchanan

text: The character of Daisy Buchanan is also often referenced in popular culture in terms of Jazz Age and flapper aesthetics. In the wake of Baz Luhrmann's 2013 film which featured Daisy with a bob cut, certain versions of the hairstyle were retroactively associated with the character. Consequently, the character's physical description has become synonymous with 1920s glamour.


title: Daisy Buchanan

text: The first actress to portray Daisy Buchanan in any medium was 24-year-old Florence Eldridge who starred in the 1926 Broadway adaptation of Fitzgerald's novel at the Ambassador Theatre in New York City. The play was directed by future motion picture auteur George Cukor. The production delighted audiences and garnered rave reviews from theater critics. The play ran for 112 performances and then paused when its lead actor James Rennie traveled to the United Kingdom to visit an ailing family member. As F. Scott Fitzgerald was vacationing in Europe at the time, he never saw the 1926 Broadway play, but his agent Harold Ober sent him telegrams which quoted the many positive reviews of the production. A year later, Elderidge married film actor Fredric March in 1927.


title: Daisy Buchanan

text: In the footsteps of Florence Eldridge, later actresses have portrayed Daisy Buchanan on the stage. Heidi Armbruster portrayed Daisy in Simon Levy's 2006 stage adaptation of Fitzgerald's novel. Armbruster's performance, according to critic Quinton Skinner, was "full of loony momentary enthusiasms and a dangerous sensuality, though by the second act, Armbruster's perf veers toward hollow mannerisms." Daisy was portrayed by Monte McGrath in a 2012 version of the same play, and her performance was met with acclaim. Madeleine Herd played Daisy in a 2015 adaptation by Independent Theater productions.


title: Daisy Buchanan

text: A number of actresses have portrayed Daisy Buchanan in cinematic adaptations of Fitzgerald's novel. The first cinematic adaptation of "The Great Gatsby" was a silent film produced in 1926 and featured Lois Wilson as Daisy. In contrast to later adaptations, the film treatment and screenplay were both written by women. The treatment was by Elizabeth Meehan, and the screenplay was by Becky Gardiner. Reviewers praised Warner Baxter's portrayal of Gatsby and Neil Hamilton's portrayal of Nick Carraway but some found Lois Wilson's interpretation of Daisy to be needlessly unsympathetic. Other critics raved that Wilson reached "heights of emotional acting in the picture which she never before attained" and did "the best acting of her career." Reportedly, F. Scott Fitzgerald and his wife Zelda loathed the 1926 film adaptation of his novel and walked out midway through a viewing of the film at a theater. "We saw "The Great Gatsby" at the movies," Zelda later wrote to an acquaintance, "It's rotten and awful and terrible and we left." The film is now considered lost.


title: Daisy Buchanan

text: In 1949, a second cinematic adaptation was undertaken starring Betty Field as Daisy. In contrast to the 1926 adaptation, the 1949 adaptation was filmed under the strictures of the Hollywood Production Code, and the novel's plot was altered to appease Production Code Administration censors. According to screenwriter Richard Maibaum, critics were conflicted about Field's performance as Daisy: "Some thought she was perfect, others that she was subtly wrong." Critic Lew Sheaffer wrote in "The Brooklyn Daily Eagle" that Field performed "the difficult feat of making a strong impact" as Gatsby's "vague, shilly-shallying sweetheart." Boyd Martin of "The Courier-Journal" opined that Field was "convincing in showing the shallowness of Daisy's character", whereas Wanda Hale of "The New York Daily News" complained that Field gave "such a restrained, delicate performance that you have to use some imagination to understand her weakness."


title: Daisy Buchanan

text: In 1974, Mia Farrow portrayed Daisy in the third cinematic adaptation. The film received poor critical reviews, and Farrow's performance as Daisy was met with a mixed reception. Bruce Handy of "Vanity Fair" praised Farrow as being "full of vain flutter and the seductive instant intimacy of the careless rich". Vincent Canby of "The New York Times", in an otherwise negative review of the film, wrote favorably of Farrow as Daisy, calling the actress' performance "just odd enough to be right as Daisy, a woman who cannot conceive of the cruelties she so casually commits". Roger Ebert lamented that Farrow played Daisy as "all squeaks and narcissism and empty sophistication." Similarly, Gene Siskel complained that Farrow interpreted Daisy to be a "skittish child-woman" who bore little resemblance to Fitzgerald's character. Upon viewing the 1974 film, Fitzgerald's daughter Frances "Scottie" Fitzgerald criticized Farrow's performance as Daisy. Although she praised Farrow as a "fine actress," Scottie noted that Farrow seemed unable to convey the "Southern nature" of Daisy's character.


title: Daisy Buchanan

text: In 2013, Carey Mulligan portrayed Daisy in the fourth cinematic adaptation. Mulligan had two 90-minute auditions, which she found to be fun and served as her initial encounters with Leonardo DiCaprio, who portrayed Gatsby. Mulligan partly based her performance on the Kardashian family in regards to "looking very present, presentational, and perfect." She was familiar with the dislike some readers of "The Great Gatsby" had for the character but felt she could not "think that about her, because I can't play her thinking she's awful." Todd McCarthy of "The Hollywood Reporter" in his review of the 2013 film wrote that viewers had their own ideas about Daisy's character and would debate whether Mulligan "has the beauty, the bearing, the dream qualities desired for the part, but she lucidly portrays the desperate tear Daisy feels between her unquestionable love for Gatsby and fear of her husband." Critic Jonathan Romney of "The Independent" praised Mulligan's "reassuringly candid presence" which he described as "weary, wan, with a dash of Blanche DuBois."


title: Daisy Buchanan

text: Phyllis Kirk portrayed Daisy in a 1955 episode of the television series "Robert Montgomery Presents" adapting "The Great Gatsby". Reviewers were lukewarm towards Kirk's interpretation of Daisy noting that her performance was "fine" and more than adequate as "the distraught lady across the bay" from Gatsby. Three years later, Jeanne Crain played Daisy in a 1958 episode of the television series "Playhouse 90". Mira Sorvino played Daisy in the 2000 television adaptation. Produced on a limited budget, the 2000 television adaptation greatly suffered from low production values. Sorvino's performance was roundly criticized. Natasha Joffe of "The Guardian" wrote that Sorvino was an abysmal Daisy "whose voice is supposed to be full of money, but is just moany. Why would Gatsby love her? She looks like a drowned goose and her hats are like they've been made out of old pants." Similarly, John Crook of "The Fremont Tribune" wrote that Sorvino was "seriously miscast as Daisy". In 2007, Tricia Paoluccio portrayed Daisy in an "American Masters" television episode titled "Novel Reflections: The American Dream".


title: Daisy Buchanan

text: Irene Dunne starred as Daisy in an adaptation broadcast on CBS "Family Hour of Stars" on January 1, 1950, and Pippa Bennett-Warner played Daisy in the 2012 two-part BBC Radio 4 "Classic Serial" production.


title: Reply 1994

text: Reply 1994 () is a 2013 South Korean television series starring Go Ara, Jung Woo, Yoo Yeon-seok, Kim Sung-kyun, Son Ho-jun, Baro, Min Do-hee, Sung Dong-il, and Lee Il-hwa. It aired on tvN from October 18 to December 28, 2013 for 21 episodes.


title: Reply 1994

text: Written by Lee Woo-jung and directed by Shin Won-ho, "1994" is the second installment of the "Reply" series. Its final episode garnered an average viewership rating of 11.509%, making it one of the highest-rated Korean dramas in cable television history.


title: Reply 1994

text: Set in 1994, six university students from various provincial areas of South Korea (Jeolla Province, Chungcheong Province and Gyeongsang Province) live together at a boarding house in Sinchon, Seoul, which is run by a couple with a daughter named Sung Na-jung.


title: Reply 1994

text: Like its predecessor, "Reply 1997", the series follows a nonlinear story telling where it shifts between the past in 1994 and the present in 2013, making the viewers guess who will become Na-jung's husband among the male characters.


title: Reply 1994

text: The series follows the historically and culturally significant events that happened in the country in 1994 and the years that followed, including the emergence of seminal K-pop group Seo Taiji and Boys, the Sampoong Department Store collapse and the birth of the Korean Basketball League. The names of the boys are revealed later, to avoid spoilers. They're mostly just referred to by their nicknames listed below.


title: Reply 1994

text: Director Shin Won-ho and writer Lee Woo-jung had originally planned for their previous TV series to be set in 1994, which was the year they entered college (Shin studied chemical engineering at Seoul National University). But they decided to change the year to 1997 after casting Sechs Kies member Eun Ji-won, since H.O.T. and Sechs Kies fandom was at its peak that year, which made an interesting juxtaposition to the failing Korean economy during the IMF crisis.


title: Reply 1994

text: Shin and Lee felt there was enough material for another series, and in a bid to replicate "Reply 1997"'s success, cable channel tvN announced a "sequel" or "second season" in April 2013. Shin said, "The stories about people moving to Seoul are full of unpredictable incidents."


title: Reply 1994

text: Despite the same writer and director, and the casting of Sung Dong-il and Lee Il-hwa, "Reply 1994" is not a prequel of "Reply 1997"; it uses the same concept of coming-of-age drama combined with 1990s nostalgia, but with a completely new plot and characters.


title: Reply 1994

text: Soundtracks for the drama consist of re-arranged popular Korean songs from the nineties. All re-arranged songs are well received by Korean general public and topped various Korean music charts.


title: The Institute (novel)

text: The Institute is a 2019 American science fiction-horror thriller novel by Stephen King, published by Scribner. The book follows twelve-year-old genius Luke Ellis. When his parents are murdered, he is kidnapped by intruders and awakens in the Institute, a facility that houses other abducted children who have telepathy or telekinesis.


title: The Institute (novel)

text: Tim Jamieson leaves his job in Florida and prepares to head to New York City. By coincidence, en route, he gives up a seat on a plane and finds himself in the small town of DuPray, South Carolina. A decorated former policeman, Tim takes a job as a local patrolman, and soon develops a relationship with a deputy, Wendy Gullickson.


title: The Institute (novel)

text: Another storyline begins in suburban Minneapolis with Luke Ellis, a twelve-year-old intellectual prodigy with mild telekinetic abilities. One night, intruders silently murder Luke's parents and kidnap him. Luke wakes up in a room almost identical to his own at "the Institute," a facility secretly located deep in the forests of Maine. The Institute houses a number of other kidnapped children, each with special talents—telekinesis and telepathy. Luke befriends several other kids: Kalisha Benson, Nick Wilholm, George Iles, Iris Stanhope, Helen Simms, and later ten-year-old Avery Dixon, in the area known as Front Half. Mrs. Sigsby, the Institute's director, and her staff are dedicated to extracting the special talents from the children - known as TPs (telepaths) and TKs (telekinetics). Experiments and torture are performed on the children to try to enhance their talents, as well as to awaken TP abilities in TKs and vice versa. Once the experiments are done, the children "graduate" to Back Half. None of the children who have gone to Back Half have ever been seen again. Luke begins to develop weak TP abilities due to the experimentation but keeps it secret. After Kalisha graduates to Back Half, she is able to send telepathic messages to Avery, an advanced TP. Luke comes to believe that in Back Half, the children's collective abilities are weaponized for assassinations until the strain kills them. Luke becomes desperate to escape and get help before he graduates.


title: The Institute (novel)

text: Maureen Alvorson, a housekeeper at the Institute, is also an informant for Mrs. Sigsby, but her financial issues cause her to seek help from Luke. Maureen thus helps Luke to escape the Institute and then commits suicide in order to help hide his disappearance. The Institute's deteriorated security takes almost a day to realize Luke's escape, by which time he has found himself on a train, which he jumps off of in DuPray. A hotel owner in Du Pray is on the payroll of those in charge of the Institute and informs them that Luke is in town. Meanwhile, Luke manages to convince Tim Jamieson, Wendy Gullickson, and other police officers of his story and gives the Sheriff a USB stick containing a confession from Maureen, along with a harrowing video taken secretly in Back Half, which convinces them to help him. Several staffers from the Institute arrive in Du Pray and, following a shoot-out, several police and all but Mrs. Sigsby and a doctor from the Institute are killed. Tim and Luke take the captured Mrs. Sigsby back to the Institute where her second-in-command, Trevor Stackhouse, tries to ambush them. Since Tim made Mrs. Sigsby drive the car, the Institute's guards mistakenly kill her.


title: The Institute (novel)

text: Whilst Luke has been away, several Back Half children, including Avery (who was sent to Back Half as punishment for helping Luke escape), round up those who have been in Back Half for longer, and whose minds are almost completely broken, and plan a revolution. Stackhouse gives orders to kill them using poison gas created by mixing the facility's cleaning chemicals. As the gas is released, Avery, Kalisha, Iris, George, Nick, Helen, and the others join together and fight back, managing to levitate areas of the Institute into the air. Kalisha, George, Nick, and Helen escape, but the others, including Avery, are killed when the corridor they are trapped in collapses. The remaining Institute staff are all killed or flee, and Tim takes Luke and his surviving friends back with him to DuPray.


title: The Institute (novel)

text: Months later, they are visited by an unnamed man, the supervisor of the Institute, who speaks with a vague lisp and explains that the children in the Institute were being used to combat those who precogs working for the Institute have seen threatening the safety of the entire world. The Institute is just one of several around the world, but all of them have had revolutions at the same time, apparently all telepathically coordinated by Avery. Luke argues with the man about the possibility of predicting the distant future, claiming that precogs can only accurately predict occurrences that happen in the near future, as there are too many variables involved over long time spans. The lisping man leaves Luke and his friends alone for the promise that the USB Stick will not come to public knowledge; the USB stick is kept hidden in a safe, with each of the surviving children holding a key.


title: The Institute (novel)

text: The other kids are slowly returned to their homes, but Luke remains in DuPray with Tim and Wendy, and the novel ends with Luke thinking about what a little hero Avery was.


title: The Institute (novel)

text: At the review aggregator website Book Marks, which assigns individual ratings to book reviews from mainstream literary critics, the novel received a cumulative "Positive" rating based on 26 reviews: 9 "Rave" reviews, 13 "Positive" reviews, and 4 "Mixed" reviews. "Publishers Weekly" gave the novel a rave review, writing, "King wows with the most gut-wrenching tale of kids triumphing over evil since "It" [...] Tapping into the minds of the young characters, King creates a sense of menace and intimacy that will have readers spellbound [...] Not a word is wasted in this meticulously crafted novel, which once again proves why King is the king of horror." "Kirkus Reviews" praised the book, though commented that it wasn't as scary of some of King's other work, saying, "King fans won't be disappointed, though most will likely prefer the scarier likes of "The Shining" and "It"." "Booklist"s Carl Hays praised the novel, saying, "King devotees will, of course, devour this latest suspenseful page-turner, but any reader looking for a smart thriller about an unusual black ops organization will find this compelling and rewarding. With his usual blend of plot twists and vividly drawn characters, King remains at the top of his game."


title: The Institute (novel)

text: Writing for "The Sunday Times", John Dugdale called it "a captivating, hybrid novel" but questioned its meaning, saying, "What it all adds up to, though, is unclear." Talking of Mrs. Sigsby and the people at the Institution, Laura Miller of "The New York Times" said "Of all the cosmic menaces that King’s heroes have battled, this slow creep into inhumanity may be the most terrifying yet because it is all too real." In January 2020, Truly Hunter said "Fans of Stephen King will likely fall in love with this book. If readers are looking for something new that feels like classic King, this is the book to pick up. It is a new take on an old premise with a classic Stephen King spin. The novel has everything King readers have come to expect and it could be the one recent King release that stands as a new classic from the author," however criticized the book's length. King noted connections between the novel and some of former President Donald Trump's actions, including "Children, seeking asylum at the border ... being removed from their parents under the administration’s family separation policy."


title: The Institute (novel)

text: On the novel's publication date, it was announced that the television rights were secured by Spyglass Television for a limited series, with David E. Kelley writing, Jack Bender directing and both Kelley and Bender executive producing.


title: Wilkes-Barre, Pennsylvania

text: Wilkes-Barre ( or ) is a city in the U.S. state of Pennsylvania and the county seat of Luzerne County. Located at the center of the Wyoming Valley in Northeastern Pennsylvania, it had a population of 44,328 in the 2020 census. It is the second-largest city, after Scranton, in the Scranton–Wilkes-Barre–Hazleton, PA Metropolitan Statistical Area, which had a population of 563,631 as of the 2010 census and is the fourth-largest metropolitan area in Pennsylvania after the Delaware Valley, Greater Pittsburgh, and the Lehigh Valley with an urban population of 401,884.


title: Wilkes-Barre, Pennsylvania

text: Scranton/Wilkes-Barre is the cultural and economic center of a region called Northeastern Pennsylvania, which is home to over 1.3 million residents.


title: Wilkes-Barre, Pennsylvania

text: Wilkes-Barre and the surrounding Wyoming Valley are framed by the Pocono Mountains to the east, the Endless Mountains to the north and west, and the Lehigh Valley to the south. The Susquehanna River flows through the center of the valley and defines the northwestern border of the city.


title: Wilkes-Barre, Pennsylvania

text: Wilkes-Barre was founded in 1769 and formally incorporated as a borough in 1806, and as a city in 1869. The city grew rapidly in the 19th century after the discovery of nearby coal reserves and the arrival of hundreds of thousands of immigrants who provided a labor force for the local mines. The coal mining fueled industrialization in the city, which reached the height of its prosperity in the first half of the 20th century. Its population peaked at more than 86,000 in 1930. Following World War II, the city's economy declined due to the collapse of industry. The Knox Mine disaster accelerated this trend after large portions of the area's coal mines were flooded and could not be reopened. Today, the city has around half of its peak population of the 1930s, making it the largest city in Luzerne County and the 13th-largest city in Pennsylvania. The contiguous network of 5 cities and more than 40 boroughs all built in a straight line in Northeastern Pennsylvania's urban area act culturally and logistically as one continuous city, so while the city of Wilkes-Barre itself is a smaller town, the larger unofficial city of Scranton/Wilkes-Barre contains nearly half a million residents in roughly 200 square miles.


title: Wilkes-Barre, Pennsylvania

text: By the 18th century, the Wyoming Valley was inhabited by the Shawnee and Delaware Indian (Lenape) tribes. In 1753, the Susquehanna Company was founded in Connecticut for settling the Wyoming Valley (in modern-day Pennsylvania). Connecticut succeeded in purchasing the land from the Native Americans; however, Pennsylvania already claimed the very same territory through a purchase they made in 1736. In 1762, roughly two hundred Connecticut settlers (Yankees) established a settlement near Mill Creek. They planted wheat and constructed log cabins. The Yankees returned to New England for the winter.


title: Wilkes-Barre, Pennsylvania

text: The Connecticut settlers returned in the spring of 1763 with their families and additional supplies. A party of Iroquois also visited the area with the dual purpose of turning the Delaware (Lenape) against the colonists and killing Teedyuscung, a local Delaware chief. On April 19, 1763, the residence of the chief, along with several others, was set ablaze. Chief Teedyuscung perished in the inferno. The Iroquois let the Delaware believe that this atrocity was committed by the settlers. As a result, the Delaware attacked the colonists on October 15, 1763. Thirty settlers were killed, and several others were taken prisoner. Those who managed to escape fled back to New England. The Delaware then burned what was left of the Yankee settlement.


title: Wilkes-Barre, Pennsylvania

text: In 1769, the Yankees returned to the Wyoming Valley. Five townships were established by Connecticut. Each one was five square miles and divided amongst forty settlers. Wilkes-Barre Township was one of the original townships; it was named in honor of John Wilkes and Isaac Barré—two British members of Parliament who supported colonial America. Pennsylvanians (Pennamites) also arrived in the valley that same year.


title: Wilkes-Barre, Pennsylvania

text: The Connecticut settlers established Fort Durkee, which was named in honor of their leader (Colonel Durkee). This was immediately followed by a series of skirmishes between the Pennsylvanians and Connecticut settlers. The land changed hands several times between the two groups. The Congress of the Confederation was asked to resolve the matter. With the Decree of Trenton, on December 30, 1782, the confederation government officially decided that the region belonged to Pennsylvania; the Wyoming Valley became part of Northumberland County.


title: Wilkes-Barre, Pennsylvania

text: Pennsylvania ruled that the Connecticut settlers (Yankees) were not citizens of the Commonwealth. Therefore, they could not vote and were ordered to give up their property claims. In May 1784, armed men from Pennsylvania force-marched the Connecticut settlers away from the valley. By November, the Yankees returned with a greater force. They captured and destroyed Fort Dickinson in Wilkes-Barre. With that victory, a new state (which was separate from both Connecticut and Pennsylvania) was proposed. The new state was to be named Westmoreland. To ensure that they didn't lose the land, the Commonwealth of Pennsylvania worked out a compromise with the Connecticut (Yankee) settlers. The Yankee settlers would become citizens of Pennsylvania and their property claims would be restored (prior to the Decree of Trenton). As part of the compromise, Pennsylvania would establish a new county in Northeastern Pennsylvania. The Yankees agreed to the terms.


title: Wilkes-Barre, Pennsylvania

text: On September 25, 1786, the Pennsylvania General Assembly passed a resolution which created Luzerne County. It was formed from a section of Northumberland County and named after Chevalier de la Luzerne, a French soldier and diplomat during the 18th century. Wilkes-Barre became the seat of government for the new territory. This resolution ended the idea of creating a new state.


title: Wilkes-Barre, Pennsylvania

text: In 1797, several decades after the community's founding, Louis Philippe, later the King of France from 1830 to 1840, stayed in Wilkes-Barre while traveling to the French Asylum settlement.


title: Wilkes-Barre, Pennsylvania

text: Wilkes-Barre's population skyrocketed due to the discovery of anthracite coal in the 19th century. In 1808, Judge Jesse Fell of Wilkes-Barre discovered a solution to ignite anthracite with the usage of an iron grate; it allowed for the coal to light and burn easier. This invention increased the popularity of anthracite as a fuel source. This led to the expansion of the coal industry in Northeastern Pennsylvania; Wilkes-Barre was nicknamed "The Diamond City" due to its high productivity of mining coal. The growing demand for coal as a domestic heat source resulted in changes to patterns of immigration to Wilkes-Barre in the 19th century. The Pennsylvania guide, compiled by the Writers' Program of the Works Progress Administration in 1940, noted that:


title: Wilkes-Barre, Pennsylvania

text: Throughout the 1800s, canals and railroads were constructed to aid in the mining and transportation of coal. Hundreds of thousands of immigrants flocked to the city; they were seeking jobs in the numerous mines and collieries that sprang up throughout the region. In 1806, Wilkes-Barre Borough was formed from a segment of Wilkes-Barre Township; it was later incorporated as a city in 1871. This was the direct result of the population boom. At its peak, Wilkes-Barre had a population of over 86,000 in the 1930s and 40s.


title: Wilkes-Barre, Pennsylvania

text: New industries were established and the Vulcan Iron Works was a well-known manufacturer of railway locomotives from 1849 to 1954. During Wilkes-Barre's reign as an industrial and economic force in America, several major companies and franchises became based in the city, such as Woolworth's, Sterling Hotels, Miner's Bank, Bell Telephone, Luzerne National Bank, and Stegmaier.


title: Wilkes-Barre, Pennsylvania

text: Even though the overall economy was doing very well, the city was still prone to natural disasters. Besides frequent flooding from the Susquehanna River, Wilkes-Barre also endured a devastating F3 tornado on August 19, 1890. The twister killed 16 people, injured 50, damaged or destroyed 260 buildings, and cost at least $240,000 (in 1890 money).


title: Wilkes-Barre, Pennsylvania

text: Wilkes-Barre is located within Pennsylvania's Coal Region. The anthracite coal mining industry, and its extensive use of child labor in the early 20th century, was one of the industries targeted by the National Child Labor Committee and its hired photographer, Lewis Hine. Many of Hine's subjects were photographed in the mines and coal fields near Wilkes-Barre. The impact of the Hine photographs led to the enactment of child labor laws across the country.


title: Wilkes-Barre, Pennsylvania

text: The coal industry continued despite several disasters, including an explosion at Wilkes-Barre's Baltimore Colliery in 1919, which killed 92 miners. The industry declined when the United States switched to other energy sources, and most coal operations had left Wilkes-Barre by the end of World War II. The 1959 Knox Mine Disaster, resulting in the flooding of numerous mines, marked the end of large-scale coal mining in the area. Industrial restructuring also caused the city to lose jobs and begin a decades-long decline.


title: Wilkes-Barre, Pennsylvania

text: In 1926, Planters Peanuts Company was founded in Wilkes-Barre by two Italian immigrants. The company maintained its headquarters in the city until 1961. In 1929, baseball player Babe Ruth hit one of the longest home runs in history at Artillery Park in Wilkes-Barre.


title: Wilkes-Barre, Pennsylvania

text: On November 8, 1972, Wilkes-Barre became the birthplace of modern cable television programming, when Home Box Office (HBO) launched over the city's Teleservice Cable system (now Service Electric Cable). Around 365 Teleservice subscribers were the first to receive the premium cable service when it commenced broadcasts. (As local ordinances prohibiting direct-to-cable telecasts of theatrical feature films prevented Time-Life from launching HBO over its New York City-based Sterling Manhattan cable franchise, the company initially sought an agreement with Teleservice to launch it on the provider's Allentown system; possible television blackout conflicts for HBO-televised NBA games, as Allentown was located within the Philadelphia 76ers's blackout radius, resulted in Teleservice electing to offer it on its Wilkes-Barre system instead.)


title: Wilkes-Barre, Pennsylvania

text: Wilkes-Barre became the site of a mass shooting on September 25, 1982. George Emil Banks killed 13 people and wounded one. Banks was deemed incompetent to be executed, yet currently resides on death row.


title: Wilkes-Barre, Pennsylvania

text: Manufacturing and retail remained Wilkes-Barre's strongest industries, but the city's economy took a major blow from Tropical Storm Agnes in 1972. The storm pushed the Susquehanna River to a height of nearly , four feet above the city's levees, flooding downtown with nine feet of water. A total of 128 deaths were attributed to the storm. Most drowning deaths were caused by people trapped in their cars. Almost 400,000 homes and businesses were destroyed and 220,000 Pennsylvanians were left homeless (as were hundreds of thousands in other states). Damage was estimated to be $2.1 billion in Pennsylvania alone. President Richard Nixon sent aid to the area, after flying over in his helicopter on his way to his Camp David retreat (on June 24, 1972).


title: Wilkes-Barre, Pennsylvania

text: Throughout the 1970s and 1980s, Wilkes-Barre attempted to prevent the damage from storms as intense as Agnes by building a levee system that rises ; completed in January 2003, the network of levees cost roughly $250 million. It has successfully resisted other threatening floods in 1996, 2004, and 2006. The Army Corps of Engineers has praised the quality of the levees. In 2006, the city made the front page of national newspapers when 200,000 residents were told to evacuate in the wake of flooding that was forecast to reach levels near that of 1972, though the flooding fell short of predictions.


title: Wilkes-Barre, Pennsylvania

text: In late August 2011, Hurricane Irene, centered off the New Jersey coast, caused the Susquehanna River to rise to flood level, but there was no cause for alarm. Then, from September 6 to 8, heavy rains from the inland remnants of Tropical Storm Lee and Hurricane Katia offshore funneled heavy rain over the Wyoming Valley and into the Susquehanna River watershed. The Susquehanna swelled to record levels across the state. In Wilkes-Barre, it crested on September 9 at an all-time record of , nearly higher than water levels reached during Hurricane Agnes in 1972. The levees protected Wilkes-Barre, but nearby boroughs did not escape, as West Pittston, Plymouth, and parts of Plains Township were affected by extreme flooding.


title: Wilkes-Barre, Pennsylvania

text: On June 9, 2005, Mayor Thomas M. Leighton unveiled his ""I believe..."" campaign for Wilkes-Barre, which was intended to boost the city's spirits. Construction began on a planned downtown theatre complex, which had a grand opening on June 30, 2006. Renovation of the landmark Hotel Sterling was being pursued by CityVest, a nonprofit developer. The expansion of Wilkes University and King's College took place. Also, the canopy and matching street lights in Public Square and across downtown were removed; they were replaced by new green lampposts.


title: Wilkes-Barre, Pennsylvania

text: The city of Wilkes-Barre celebrated its 200th anniversary in 2006. Several events, including a Beach Boys concert, were planned but canceled due to extremely heavy rains. Most of the city's population was ordered to evacuate on June 28, 2006. The Bicentennial celebration was postponed to Labor Day weekend, September 3, 2006, and was attended by Pennsylvania Governor Ed Rendell and the Beach Boys.


title: Wilkes-Barre, Pennsylvania

text: The Riverfront revitalization project (River Common), broke ground in 2007 and was completed in early 2010. It has made the riverfront accessible to the public. The area also has a new amphitheater for live performances and improved access through ramps and sidewalks. Fountains and color-changing lights have been added underneath two bridges which carry pedestrian traffic across the normally-open levee. The project stretches approximately four blocks from the Luzerne County Courthouse to the intersection of South River Street and West South Street. The River Common has since hosted concerts and charity events.


title: Wilkes-Barre, Pennsylvania

text: Since completion of the River Common, additional improvements to city infrastructure have been progressing. New crosswalks have been installed downtown, including signage emphasizing that pedestrians have the right-of-way. The completion of the James F. Conahan Intermodal Transportation Facility has added parking and relocated Luzerne County buses from their former Public Square staging sites. This has reduced traffic congestion around the square. Private carrier Martz offers coach bus service from the terminal as well.


title: Wilkes-Barre, Pennsylvania

text: The widening and realignment of Coal Street, a major road connecting Wilkes-Barre City with Wilkes-Barre Township, was completed in 2012. The new Coal Street provides four lanes over the original two lanes, making travel between the highly commercial Wilkes-Barre Township and the city much easier. In 2013, Hotel Sterling was demolished due to flood damage in the hotel's basement (which compromised the building's integrity). As of today, several buildings are in the process of being constructed on the site of the former hotel.


title: Wilkes-Barre, Pennsylvania

text: According to the U.S. Census Bureau, the city has a total area of , of which is land and , or 4.60%, is water. The city is bordered by the Susquehanna River to the west. Most of Downtown is located on a wide floodplain. Floodwalls were constructed to protect a large percentage of the city. The elevation of the downtown area is about above sea level. As you travel inland, away from the river, the elevation rises. Wilkes-Barre Mountain is a physical barrier southeast of the city.