皆さんおはようございます こんにちは 今ご紹介いただきまして石蔵岡です どうぞよろしくお願いいたします今日はですね 散々デジタルエヴォルテューションウィーク2021の4日目でHow to Accelerate DXというタイトルで デジタル担当大臣台湾のデジタル担当大臣のオードリー担さんをお招きしています私もとてもこれを楽しみにしているんですけれどもオードリーさんについては皆さんよくご存知だと思うので このスライムで聞いていますが今まで本当にいろんなことをされていて 今はデジタル担当大臣としていろいろなことを進めていらっしゃるという感じですね私は今1つ橋のなんとかって書いてありますが 実はフリーターで今どこの組織にも属していなくてですねいろいろなことをやっているというのが実情で 特に若い人に対してのいろいろなことをやりたいなというかやっていますということなんで 今日はそのあたりも結構オードリーさんにいろいろ伺ってみようというふうに思っていますそれではこの辺から英語でやりますので 英語の準備をしていただければと思いますオードリーさん ありがとう very much for coming and taking time from your busy scheduleWe really appreciate having you and we have a lot of questions that we would like to askand if you could share your experiences, I think it will be greatAs a starter, I think DX, the Japanese government have been very much involved and encouraging DXThis digital transformation at the same time, I hear that a lot of companies in the private sectoris making DX as the big big slogan so to speakAnd for the government we have set up the new agency exclusively for digitalizationand we do have the minister in charge of itand the private sector is doing a lot of things depending upon what kind of industry, what kind of companies they arebut at the same time I'm a little bit concerned that we have been advocating this concept quite extensivelybut when it comes to whether that is going to be implementedand that leads to the tangible outputI have a little bit of a concern because we are very good at advocating and proposingand yet we are a little bit behind in terms of the implementationSo let me start off with the question of what are the critical elements to make the digital transformationproduce the results and make it happenCertainly, thank you Yoko for the questionMy job as the digital minister is not the IT ministerand I often make this clarification to many Japanese media because they used to call me the IT daijinand the difference is that IT connects machines and digital connects peopleso the necessary critical element of digital transformation is not to confuse it with ITif the work that you do brings people together, give voice to people who didn't have voicemake participation bi-directional, omnidirectional, multidirectionalrather than just people listening to one or two radio or TV stations and so onincrease the symmetry, the bit-rate of participation and engagementthen you are on the right path of digitalizationotherwise if you connect everything but still only one or two persons speak and everybody just listenthat's maybe digitization but it's not digitalizationit's not truly digitalOk, I think one of the things that you mentionedand I have heard your I watched your video as well as read your bookand some of the things that seems to be missingparticularly in Japan is that you talk about four pillarsand particularly these days, sustainability, innovation and inclusionand inclusion part is as you mentioned, you know, sharingand just make sure that everybody is involved rather than one or two peopleis critical and yet that is notI don't really see that clearly in Japanhow do you make sure that inclusion is everybody's businessThis is a great questionIn Taiwan, what we are doing is making sure that even people who are not of the voting ageyounger than 18 years old have full participation rightsthrough digital platforms to initiate, for example, petitionsthat cause for banning plastic straws on bubble tea drinksthat started by a 16 years oldand when I ask her why are you starting this movementshe's like this is our civic class assignmentSo the idea of inclusion begins with the basic educationand I think it also extends to lifelong educationbecause we see the most active group on our participation platformare 16 and 17 year old and 60 and 70 years oldso the silver hair and the young people are the two natural groupsthat care more about sustainability, about future generationsso if you make sure that these two group of peopleare in natural partnership with one anotherthat you are of a very good start in inclusionyou mentioned that the inclusion starts very early age16 year old girl talking about the strawbut is there any way that we can accelerate thatit means that we really have to gowe have to work on the education in early stageand it's going to take a little whilefor us to see the result of that inclusionthe concept of inclusionto be instilled in the younger generation kidsfor exampleso is there any way that we can just kind of fast trackyeah definitelyI'm sure that in Japan there's also plenty of very young peoplemaybe they're just 14 maybe they're just 15already starting a very good social movementsocial entrepreneurship and so onso in Taiwan our fast track is just to invite these young peopleto the cabinet level youth advisory counciland this council very interestinglyall appoints the people younger than 35some of them in their 20sbut they are already quite well known onlineand by calling them reverse mentorsadvice to the cabinetsthey get this natural positionthat goes against the existing discrimination based on agebecause instead of calling them young friendswe call them advisoractually the 16-year-old girlthat started the petition is now 19-years-oldand she is already advisorin the committee of national open government partnershipthe national action plan committeeand so I would call her the councillorso councillor Wangand even though she's not technically speakinga fully an adult yeta couple of questionsin order to make sure that the young peopleare placed in thegiven the position or the assignto the position of making decisionswe need like existing leadership groupsort of changing their mindset or whateverwilling to make sure that you involvethese people with new ideasand I'm not really sure whether that'sthat's not that easy because they havebest of interestand they may bethe reference point may be much morelike with their experiencesrather than today's digital nativeso how can we convinceor do we need to convince thesepresent sort of leaders of todayor leaders of todaythis is where the partnershipwith the silver haired people begins to showits importance for if the young people havethe support of the 80 years oldlike my grandma is 88 years oldthen those elderly people can actuallyspeakwith authority about the necessityof including young peopleone concrete example is that every yearour office hires very young peoplesome of them like 18 years oldinto our internship programbut initially all they did is to helpthe government web servicesto work across browsersbecause many older peoplethey're not that versed withkeyboard or internet explorerthey're more versed with their phonesor more natural ways of using tabletsand so on touch screenbut the government web services was not initially designed for thatmaybe they're designed for active actsor something like thatand so for the first couple yearsit's to make our government web site accessibleespecially to the elderly people who rely moreon touch screen and speech interfacesand that won the support of the elderly peopleand the career public service and the leadershipsee the young people as someone who assistsnot just criticizes and that builds a very goodintergenerational solidarityI'm just getting off a little bit from thethe questionsdo you think that the COVID-19accelerates that kind of trendbecause the reason why I ask that question is thatbecause of COVID-19 we're not able togo to the office or the senior peoplecould encodehave an opportunity because they can't really meetwith their friendsI think they have an incentiveand they're encouragedand I think that some people, some elderly people, old peopleare getting much more into internetbecause they want to keep in touch with the other peopleand yeah, so that may bea very good factorsort of a benefit of this COVID-19even though that restricts our movementYes, I think that transformation by necessityis definitely the caseactually many elderly people that I metespecially people in senior leadershipthey didn't want to tell a conferencenot because they cannot do itbut because they used to do that when they were youngand the technology was very bad at that timeso they remember how bad it waslike meeting face to face builds 1% trustbut a meeting ally deducts 2% trustand so because of thatthey don't want to video conferenceso COVID-19 is a great way to clean the cashlike the browser cash in their mindtheir stereotype about videoconferencingand they see nowadays with 5Gwith Wi-Fi connectionwith anyone's smartphone camerasactually it's very easy to set up and it actually brings peopleactually brings people closerrather than push people apart as they remember 10 years or 20 years agoand so this new familiarity I thinkis a great opportunitythat's very encouraging and I think that whateverthe opportunitywe should be able to take an advantage oflet me change the subject a little bitwe're talking about DXwhat kind of society do you expectwith the DXif DX proceedsI think that digital transformationwill make peace between the generationswe talked about people who are maybetwo or three generations apartbut the digital world also shows ushow the future generation will benefit or sufferthe future generationstoo often these are not visualized wellthese are not communicated wellso people cause pollution, climate changethis information that causes social upheavalwithout fully understanding the consequencesbut if we give voice and build an internet of beingsthen we can empower future generationswho are not even yet bornwe can have a full understandingof the consequences of our actionsand therefore make much more longerthinking which was previously impossiblethis is like how I experienced in virtual realityI put on virtual reality for the first time in 2016and saw the earth from the international space stationand suddenly all the borders disappearand when we are down there because of thecloudwe can't see other partsof the world very clearly but on the spacewe are much more holistic and we see the earthas an interconnected whole and this isessential if we are going to solve structural issuelike carbon dioxide that doesn't care about bordersactually the virus of the mindthis information or the virus of the bodythey are also cross border so to solve those cross border issuesrequire an intergenerational cross border thinkingand that's what digital transformationcan bring us like better telescopesI said great because I'm verycrazy about the universe and spaceand my favorite destinationafter the COVID-19 is to go to theinternational space station and stay therethere you gohow would you describe thetaiwan's position in the world with theex in the future in like three years five years outsure I think in three yearstaiwan will grow toward the skyto our international space stationwe grow by two and a half centimeters a yearso in three years that's what 7.5centimetersthe reason we grow and I guess it's relevanttoday is because of earthquakesin Taiwan we understand how badit could be for the earthquakes and the typhoonsand compound disasters so our developmentstrategy of digitalization is coupled withthe idea of resilience resiliencemeans that we build digitalizationnot to blindly develop one measurelike GDP or whateverbut rather make sure that each corner of our societyis well equipped with democratized toolsto respond in time if there is anunforeseen earthquake or typhoon orCOVID or things like that so I think inthree or five years time will be much moreresilient compared to what we have nowbecause just as we learned in 2004 after2003 we installed this central epidemiccommand center as response to newrespiratory diseases so we will buildcenters of excellence to respond to theemerging issues out of full digitalizationsuch as for example state sponsoredmalicious hackers that has beenactually all over the news over the past couple monthsthis is also something that we will build resilience towardIsa very interesting what would be yourindividual goal three years five years outor ten years can you share it with ussure I plan to visit Japan after theCOVID and meet you face to faceand maybe immerse myself in a newlanguage I really want to learn nihongo I currentlydon't speak the language but I would really want to learn that and beyondlearning the language I foresee that my job will take meto work more cultures around the world becausenowadays for the past year or so I wake up inmeeting in one time zone and throughout the day I move time zonesand by the evening I meet with the European and Africanpeople and so on so this is like touring around the world in a virtual wayand this really builds a more transcultural mindsetin me compared to the pre-COVID days so I look forward tovisit these cultures in real space once the COVID is overI see well when it comes to the language I hear youtalk to the young people and fromPohoku and we're in Japanese so I knowthat those big Japanese as wellI was reading of a script to be honest to be honestbut yes I'm really meaning to do thatjust changing the subject a little bityou have done tremendous things andaccomplishment so far if you are able todo it all over again would you do something differentor would you sort of follow the same thingyou talk about the resilience and learning from SARS and all sorts of thingsbut what you know nowdefinitely I will make a couple changesthe first one is that I think we will make surethat the open API initiative is wrote out even soonerbecause we helped rolling out the open data initiativein 2012 2013 and by 2014I'm well integrated into the open data landscape in Taiwanand at the time of the open data council in the national development councila committee but however what we are now seeingis that if we push open API before open datait actually lowers everybody's riskbecause if you push open data and a public servant needs to review itbefore publishing it creates more work for themit's more risk for them if things go wrong and they get less trustfrom people if things go wrong but if we push open APImeaning that data is published as soon as it's collectedwithout human review or human interventionthen it saves their time it builds trust and when people criticizeabout the data quality or data pipeline everybody can offerthe solutions together and no public servant would besaying this is a waste of time because it didn't spend timeto begin with so I would begin the automated API basedopen data much sooner than beforethan what we actually did in 2016 that's the first thingI will change the second thing that I will change in my waysis to make sure that the public service holds thediscussion themselves previously in 2012 2013we rely on the outside people to chairthe communities of transformations and so onbut it turns out the career public service already knowhow to make such changes it's just they weren't given the mandatethe authority so we switched by 2016 into aone by one like reverse mentorshiprelationship where the young people the outside experts reversementor a career public servant but it's the career public servantthe actual plans and so this makes sure that they internalizethe digital transformation instead of seeing theseoutside experts as contractors and so on they have tosee through this end to end process so that's something we couldhave introduced in 2013 or 2014 but we waited until16 to introduce it I will also begin that soonI see you mentioned the sort of the importance of trustin many aspects of the digital transformationdata and particularly so because we have so much informationand some of them are not you know facts andat the same time I think we are not quite sureit's not very clear to me whether the trustis we do have trustthe amount of trust that we need to go onand my question is that trust is very difficult to buildit takes time and you can lose it veryvery quickly but it does take a lot of timeto build you have any suggestions I thinkright now we have a little bit of a government you know private sectorand the people who may trust you the media who maynot trust and vaccination and all sorts of thingsany suggestions as to how to build the societywhere the trust we talk about the importance of trustbut when it comes to how to build itit's a very challenging taskyes our habit is to invite peoplewho criticize into the decision making processso people who criticize actually care about thisotherwise they wouldn't bother criticizingand my favorite question to ask is if you are the digital minister thenwhat would you do and if they have a good ideaI apologize very quickly I'm okay apologizing and I say your idea will becomenational policy by next Thursday because we use the agilemethod we deploy every Thursday that's our screen our iterationso anyone who can call the toll free numbermore than 2 million people called that number last yearthey understand if they have a really good idea chances arethat the minister me or minister or the cabinet ministerswill acknowledge their contributioninvite them into the decision making process and because they feel they are partof the solution they wouldn't write off the trustthey can criticize about our incompetence but oncetheir idea become our policy then of course the criticizebecome constructive criticism then it's not aboutattacking each other canceling each other's trust so I thinkthe two most important thing one is a very quick iterationif they have to wait a year of course there's no trust anymoreand the second is this swift apology if I did something wrongI just apologize very quickly and say next Thursday your idea will become the policythis quick iteration is somethingthat I don't quite see hereand I think that's key to this whole worldand at the same time to build the trustand I'm not quite sure I think wethings are changing to some extent so I have a hope and I'm optimisticbut we tend to sort of postpone it keep it offuntil we know what works or we havemore information and let's decidewe can think of quite a few examples right nowwe haven't made any decisions or we haven't done anythingeven though we sort of know that's the direction that we're goinghow the quick iterationis not something thatis something that you built or you knowhow did you make sure that does help take placeor hasn't been in time yetwe need to institutionalize itwe are both democratic polity so we already have a iterationit's just voting is very longit has a very low bit ratewe need to give or take a couple of bits so the bit rate being so lowit makes people not care abouteveryday decision making or collective intelligencebecause they wouldn't think that their contribution, those three bits per four yearsactually have such a good contribution to the societyso what we could do is to install newhigher bandwidth types of technologyfor example the petition websitejoin.gov.tw just like how amazon will recommend youbooks to read based on the books you have readbased on the petition you have signed the platform will suggest you other petitionsthat you might be interested ineveryday you can start a petition join a petition and so onand increase the bit rate of contribution and you can also of coursecriticize offer alternate ideas to a petitionbut we make sure that while you can comment on the contrapanel and you can support it on a four pro panelthese two panels cannot reply to each otherso people don't waste time to criticize and attack each otherthey spend time on the issue at hand and upvoting or downvotingbut they do not waste time cancelling each other offpro social media so if we design the digital public infrastructureso it's pro social then it's fun so people will participateso the key to more participation is to make the response fastmake the response fair and also make it funand if it's fast, fair and fun people spend more time on democracyand with higher engagement naturally you get into a placewhere people feel shorter iteration is just fine because that'swell we are used to responding anywayvery interesting and I thought I was like reply buttonis not there is a I think it's a very very interestingand device that makes sure that you know you don't criticizeyou go back and forth and back and forth which seems to be gettinganywhere so but let me ask youlet me go back to this young generation sort of engagementyou have done this incredible job of engagingthe younger generation and in JapanI think you talked a little bit about the lost chapter of your bookwhich I read and the Japanese young peopleeven though I really do count on thembecause they are the ones who are going to create the futureand they're going to be around I'm not going to be around20 years from now hopefullybut it seems like they are not as engagedand I'm not really sure whether they are not interestedor they don't feel that whatever they saymakes a difference and also they're not as engagedparticularly for the other movement as you did in Taiwanand so what would I doI think rather than justcriticizing the young generation don't have anything to sayyou really need to make sure that you encourage themto participate and make surein a way I do believe in do as I dorather than do as I sayany suggestions as to the older generationthat sort of 30 years olderYes, speaking as a 30 somethingjust for another month or so I turn 40 the next monthspeaking as a 30 somethingI think this is a critical question because the young peoplethey are digital native, they think in terms of the digital worldthey think in terms of the open spaces onlineactually feel that's close to their neighbors unless their neighborssomehow makes them feel that their suggestions makesense otherwise they're much more interested in influencingtheircommunity neighbors online which feels much closerto them so I think that idea of neighborhood of communityreally changes with the digital world and I think theway to fix this is actually very simple it isjust to make sure that their immediate neighbors people in the same townshipand so onactually look for the guidancethe direction, the digital transformation from the young digitalnatives so I always say to the youth advisorsthat you decide on the direction and we providethe resources and together we will form a vectorthey decide where to point and we make sure that we go thereand so the people who are youngthey actually are there's no shortage of new directions to gobecause they're very well connected they see the best practicesor better practices in other corners in the world and they areok translating introducing it to the people around themso asking them to become for example social entrepreneurswhile absorbing the risk of failure by the education facilitythat's what the Taiwanese people do we make sure that in theirundergrad studies they can use their startupas a undergrad capstone project making sure thatthe initial investment capital if they have to pivotis absorbed by the education budget and things like thatso they can try quite a few new things using crowdfundingand then if they fail spectacularly which they probably willfirst couple tries they will write it up as field papersand also contribute to the sciencesso to make sure that there's no risk in failure I encourage the young people to care moreabout their immediate neighborhoodI think you talked a little bit about education and school and so forthwhat would the school and education system with the DXlook likeI think the campus the idea of the place where we learn togetheris going to be like everywherethe promise of digital transformation is that it frees usfrom the fixed structure the physical structurethat constrain the number of people who can listen to each otheron the online space there's no such boundaries so peoplewell aside from time zones and the sleeping pattern but other than thatthere's no easy burdenthat's put on people's mind if we say let's just connecton video conference you don't automatically thinkwhat about travel what about commuting what about busschedule and things like which tend to complicate thingswhen people need to meet with people they barely knowso the weak links can form strong links online much moreand gradually too rather than the immediate burdens that people thinkabout in the physical world and the same applies to educational institutionsindeed the whole city the whole country the whole worldmaybe a campus and their classmates quote unquotemaybe people in different sectors in different age groupsin different disciplines and so on as long as they share a commonvalue so I think education in the future will concentrate on the common goodon the things that people consider important regardless of their ageor culture or place differences and then the digital transformationwill form a study group with people who care about the same valuerather than just happen to share the same neighborhoodI see so that opens up tremendous opportunitiesfor a lot of people to connect and do things togetherI see collaborate I think collaboration is one of the key things that youoften mention and sharing and so forththen the question is what happens I mean I loveto ask questions what if what if digitalizationand digital things disappear oneday so it means that it goes toquantum or something right so it's no longer digitalright we have analog ministers and then digitalminister maybe we'll have quantum ministers in a few yearsyeah I think that the world is lookingtoward new ways of conversations of communicationand these are the core human needs be it the analogtechnologies of pen and paper which are pretty good by the wayor the digital technologies like the video conference were havingnow or maybe one day the quantum technologies ofsecure communication that cannot be eavesdropsor direct links between the quantum states of our brainsso that we can feel each other's emotions better and so onI think the common hope is to link people together as you said to collaborateand digital or the digital tools are just a faceit's a instrument someday maybe quantum or non-digital waysare we replace this generation of toolsthat'll be very interesting I agree that digital is just a meansand yet I think we a lot of people tend to thinkthat the digital is it without thinking about what kind ofsociety what kind of things you would like to do andthat's something that we have to get awaybecause it's much easier to think about and measureif we are talking about how tos or techniques or methodsbut we really need to think aboutwhat kind of society, what kind of world we would like to createhow does the individual happiness fit inwe talk very often about thiscreating the common good andhow does the individual sort of happinessfit init's a positive cycle if I feel happymore able to shareand if I'm happy on average even on the time where I'm unhappyI'm motivated to write why I feel unhappy and what I did to make myself happierand share it with the worldthe more base happiness the more sharingit makes a supportive environment to make it easier for people to feel happyhappiness this joy this fun feeds into this cycleso I think the importance of individual happinessis not that you have to feel happyit's just you need to mingle with the community that's on average happyand then you can support the community and the community can support youthat's very good and becausewe tend to thinkeverything in terms of the conflictonline offlinebut I think what you're saying is that it's much more comprehensiveas we talked about inclusiveand so that's the kind of thing that we're talking about individual or the other society or the worldlet me change it since we have about two more minuteslet me talk a little bit about private personal mattersyou describe your day and the bookin a very clear way you walk to the placeyou make coffee, ice and all sorts of thingswhat comes to your mind when you start the dayyes when I wake upI look at my surroundingsand I write down often with this stylusthe things that I learned in my sleepbecause I read material without passing judgmentgoing into sleep so I often wake upwith a new idea that brings those different things togetherfor example you mentioned about this versus thatso I would sometimes go to sleep thinking about acomment that I read actually Tyler Cohen's blogat one day where a commentator saysshe also says she's non-binaryhow can a digital minister be non-binarybecause we know digital world is a binary worldI would fall to sleep with thatand I write down my comments to thatI actually did write that down and I saiddigital is not binaryit could be decimaldigital is also digitalin our mind there can be more than one valuethis plurality is also digitalthis is the kind of thing that I wake up withand then I just write it downI think that is something that I found in yourtalk or in the bookI think that's by far the most important thing for mebecause I think that while you sleepyou read all the things before you go to sleepand in the morning you have key phrasesI'm going to practice itwhether that works or notI think we're just running out of timebut thank you so much for such an inspiringand such an exciting talkand I do appreciate it very muchand I hope we will meet in personto meet with all sorts of people in realworldThank you for the very enjoyable conversationThank youという事で今回の踊り炭酸とのセッションはこれで終わりましたとても面白かったと思うので皆さんも色々参考にして頂ければいいかなという風に思いますありがとうございました


Colgate dental cream to clean your breath while you clean your teeth and help stop tooth decay and Luster cream shampoo for soft glamorous Corressible hair bring you our miss Brooke starring Eve Arden It's time once again for another comedy episode of our miss Brooks under the direction of Al Lewis Well, this is National Pickle Week and among others who celebrated the occasion was our miss Brooks who teaches English at Madison High School I celebrated National Pickle Week. All right by getting myself into the prettiest pickle. You've ever seen It all started innocently enough when my landlady and I sat down to breakfast last Thursday morning There's your cereal Connie Now tell me dear have you made any plans for your vacation next month? Nothing definite, Mrs. Davis Perhaps it's just as well not to plan too far in advance. Who knows what summer may bring you might even elope Have you ever thought of that Connie many times Mrs. Davis? I do it in a minute too if it weren't for a stubborn little streak in me Which keeps insisting that it's no fun to elope by yourself. I Didn't mean by yourself Connie. What's wrong with mr. Boynton for submitting the outstanding question of the week We are sending Mrs. Margaret Davis a lifetime supply of Dutch boy paint. I Wish I knew what was wrong with mr. Boynton. All he talks about lately is his impending vacation in South America South America what a wonderful idea and it simplifies everything it does of course if mr. Boynton is going to South America That's where you have to go the thought has occurred to me Mrs. Davis, but there's one thing that stands in the way transportation transportation. Yes, one of my water wings has a blowout Don't be discouraged by your present financial state Connie I'll go make some tea and read your tea leaves in a little while Maybe there'll be some good news in your cup. Why at this very moment lady luck may be camping on your doorstep Well, don't sit there lady come on in Thank you most generous and observant pupil sit down Walter and have some toast and jelly What kind of a plant is that you're holding? It's a rare black orchid mr. Brooks here an orchid must have cost you quite a bit of Money, Walter. Pish-tush the blossom cost me nothing Besides, this is no time to concern ourselves with petty monetary considerations I'm going to be rich mr. Brooks wealthy beyond all dreams of avarice the fabulous treasures of the universe are within my grasp Say buddy, could you spare a round-trip ticket to South America? I'm serious mr. Brooks I've discovered uranium uranium where on my shoe Who's your boot black It's no joke mr. Brooks. I made the discovery in the chem lab. We got a brand new Geiger counter and it's By the way, have you ever used a Geiger counter? I haven't had to Walter very few of my pupils are named Geiger I'm afraid you don't understand a Geiger counter is an instrument that measures the number and intensity of emanations from radioactive substances sounds terribly talented But how did you get mixed up with it? Well, I climbed on a desk to fix a light bulb and my shoe got near the Geiger counter You should have heard it it almost blew its top that means uranium's on my shoe now the way I figure it all I've got to do is retrace my steps of the past few days Wouldn't it be easier to just start mining your shoe? Please miss Brooks. No, you've got to help me You see the counter is schooled property and can't be removed from the building without mr. Conklin's permission But if a teacher were to ask him not me walter I'd like to assist you in this project But now is the wrong time Tuesday I knocked a bowl of soup into his lap in the cafeteria and last week. I dropped a typewriter on his foot Oh Say it's almost 8 15. I better park this orchid in the icebox and get ready to leave Have a glass of milk. Walter. I'll just be a minute. Okay, miss Brooks. Oh It's you Connie the tea is almost ready. I'm afraid I won't have time for the reading Mrs. Davis I just want to put this in the icebox.  It won't do anybody any good there Why don't you take it down to school with you and give it to mr. Conklin mr. Conklin? Yes, you told me yourself. You've been naughty lately Maybe this little gift would make up for your recent habit of dropping things on him say it might at that Although I wouldn't want walter to find out that I gave away his present Walter wouldn't mind besides he won't know anything about it I'll just put the flour into this box that the clean laundry came in tie it with this red ribbon and Presto, you've got a peace offering for your principal. Thanks, Mrs. Davis I'm sure nothing could make him happier unless I was tied up in the box Gosh miss Brooks. I wish you'd reconsider my proposition about that Geiger counter If you'll just get his permission to use it, I'll make you a 50-50 partner and whatever we find It's a more than liberal offer walter, but I'm afraid I can't take advantage of it right now I'm trying to figure a good method of stowing away to South America Well, all right miss Brooks, but I hate the thought of passing up a passable bonus of $10,000 offered for discoveries of uranium I know walter and I can't say that it's altogether impossible, but as far as the immediate futures concerned Did you say $10,000? And if it's a big field we might even get ten times that much open the throttle Casey and point me at mr. Conklin's office I've finished straightening up your office. Thanks Harriet run along child. Isn't there anything else I can do you can leave me alone? I'll get to your first class daddy. You're irritated this morning Harriet. You're another Ellery Queen It so happens that some bandal broke into my garden trampled my flowerbeds and stole a rare black orchid I just found out about it myself I've been nursing that plant along for seven years I was planning to give that orchid to your dear mother. It's her birthday today. You know, yes I know now. I'll probably have to buy a present for the old. It's a hard gift If I ever get my hand on the scoundrel who'd enter Good morning, mr. Conklin. Oh, it's you. Hi, miss Brooks. Hello Harriet I was just leaving the office miss Brooks trying to cheer daddy up a bit. Well, you he's rather low this morning I'll see you at lunch daddy. Bye. Bye Well, mr. Conklin, isn't this a bright and cheerful morning be brief miss Brooks What brings you to my office? I just came in to leave this little gift gift. Yes, sir May I put it on your desk? If you think you can do so without knocking the typewriter off on my foot again What else mr. Conklin? I should like your permission to borrow the Geiger counter from the chem lab Geiger counter I believe that's what it's called. It's used to indicate the presence of uranium Miss Brooks, are you planning to pelt me with an abomb? Certainly not mr. Conklin. I couldn't even lift an abomb But I've heard that there's quite a reward for discovering new uranium deposits and I thought I'd kindly leave the premises but mr. Conklin I I am in no mood to discuss this nonsensical project at this moment I've had a most difficult morning nay a shocking morning. What happened mr. Conklin? I don't know how versed you are in things botanical miss Brooks. Oh, I'm pretty versed Several years ago I purchased a rare plant for the first few years it failed to bloom I tried everything finally I ceased to rely on the hit or miss methods of plant propagation employed by a bunch of buzzing bees and I pollinated that plant personally Do you realize what that entailed?  Yes. I mean no Some van will stall it Well, I guess I better be running a lot Miss Brooks, where are you taking that box? I thought you said it was a gift Oh, it is a gift mr. Conklin, but not for you. That is not actually it's for mrs. Conklin her birthday You know just a little remembrance. Well, you can leave it here. I'll take it to her after school I'd like to see what it is before Oh, no, I I'd rather you didn't see it mr. Conklin. That is well, it's uh underwear That's all right.  Would you please make a confidential note of the party's name? Confidential. I won't even read it to myself Now in this book starring Eve Arden will continue in just a moment, but first here is mern smith Now tests published in authoritative dental literature show that when teeth are brushed right after eating Colgate natto cream stops tooth decay best two years research at five leading universities Hundreds of case histories shows that when used as directed colgate natto cream stops tooth decay best Yes exhaustive tests show the colgate way best to prevent decay Better than any other home method of oral hygiene known today based on both clinical and x-ray examinations The colgate way stopped more decay for more people than ever before reported in all denifers history Even more important. There were no new cavities Whatever for more than one out of three who used colgate dental cream as directed think of it Not even one new cavity in two full years No other dentifers paste or powder ammoniated or not No other dentifers has proof of such results The best results ever reported for a dentifress of any type So always use colgate to clean your breath while you clean your teeth and remember when you follow the colgate way Colgate dental cream stops tooth decay best Well, my morning classes passed without any undue noise from the principal's office So I assumed that mr. Conklin hadn't found time to open the box containing his own black orchid So thoughtfully provided for me by walter denton when lunch period arrived I hurried to the biology laboratory to let mr. Boynton in on the ground floor of my predicament Busy mr. Boynton. Not at all mr. Brooks. Come on in before we go to lunch. There's something I'd like to talk to you about It's really silly. I guess but I was rather embarrassed this morning embarrassed It all started when walter denton came to pick me up and told me some ridiculous story about finding uranium on his shoes Oh, that isn't completely ridiculous mr. Brooks as a matter of fact It was more or less confirmed in the chem lab by the reaction of the geiger counter You mean that walter did actually step into uranium? Well, not necessarily. It could be some similar radioactive substance You realize of course that the geiger counter is an extremely sensitive instrument It'll even pick up emanations from your radium dial wristwatch all the way from fishers pawn shop It's a wonderful invention and while walter's shoe may not necessarily indicate the presence of any large field nearby It's still a rather provocative incident. I'll say it is half of ten thousand dollars is very provocative If one were to discover some uranium one would never miss the money it cost for a summer vacation would one Well, I should think not I'm going to south america myself South america That's funny. I'm going to spend my vacation down there. You too What a coincidence When are you leaving the day school ends june 23rd?  What cabin will you be? Oh, no It just meant that if we're going to be in brazil at the same time it ought to make it very pleasant for both of us They say the nights down there are very conducive to romance Yes, I've heard something of that effect in fact on most june nights in brazil The stars seem to be so low in the sky that you can reach out and touch each other Please mr. Brooks. I I I don't like to change the subject but not much you don't That's all right. Mr. Boynton brazil can wait. What is it you wanted to say? Well, I'd like to show you just how the geiger counter reacts Mr. Keller has a tiny sample of uranium in the chem lab. It's usually under lock and key though and Hi, mr. Brooks. Mr. Boynton. Oh, hello. I just dropped by to take another look at the geiger counter Eh, did you tell mr. Boynton about the swell black orchard? I gave you mr. Brooks I was just about to Walter gave me a fine black orchid this morning, mr. Boynton a black orchid Say that mighty rare must have been cultivated for about seven years most likely in a hot house This one is hotter than that Walter I don't usually give away presents But I think you ought to know that in trying to get on mr. Conklin's good side I gave him the black orchid you gave mr. Conklin I better get a glass of milk. I don't feel so good Just a minute young man. Why did you steal that flower for mr. Conklin's garden? It wasn't really stealing. I was only getting even every time mr. Conklin passes our house He strolls through the gate and gloms a rose for himself Well rose glomming isn't orchid glomming Besides, why did you have to make me the fence the fence receiver of stolen good? I've been reading a lot of Chaucer lately I'm sorry about the whole thing mr. Brooks, but tell me what did mr. Conklin say when he saw his own orchid Luckily for both of us. He hasn't opened the box yet. Well, and maybe if someone could get into his office you too That's just what I was thinking you too I just saw Harriet in the hall of course she doesn't know about what I did but she told me your dad went shopping Then maybe we can remove the plant before he comes back exactly and I've got a scheme that'll make it impossible for old marble head Mr. Conklin To incriminate any of us Are you with me? What's the layout Louis?  Conklin's bound to find out it has no roots when another orchid fails to grow Maybe so but in seven years we can cook up a dilly of an alibi I'll keep a watch here at the door miss Brooks. All right, mr. Boynton now hurry walter We've got to get that box off mr. Conklin's desk before he gets back. Okay, miss Brooks There I've got it. He's coming down the hall. We better get out of here It's too late. He'll see us quick. Get rid of the box. What box the one you're holding walter Here you are mr. Boynton. All right. Yeah, I don't want this Here miss Brooks. Here's a nice orchid for you for me. How sweet of you miss. What am I saying? Here you take this walter. I'm allergic keep it Quick quick miss Brooks toss it out the window the window. Where is it? Oh right here open. Thank goodness There you go. Hello. What's everybody doing in miss Brooks? May I inquire what it was you just threw out of my window? Who me? That is your name, isn't it Brooks? Or do you shot put under a nom de plume? Well, I do remember tossing something out, but it it was just a little bug a bug. Yes, sir That's just what it was. Mr. Conklin a bug. We all saw it didn't we mr. Boynton? Oh, yes. Yes, it was a bug mr. Conklin in my office. What sort of a bug was it a beetle a ball we've three of them were building a nest A nest?  You must get awfully tired of watching football games, don't you? Pre-doing in my office. Well, sir, we just came in to wish your wife a happy birthday You came in to wish my wife a happy birthday. Yes, sir. Happy birthday to her. Happy birthday All quiet! And I might as well tell the truth. I wanted to give Mrs. Conklin her present myself That's why we entered your office, but then when I heard you coming I became nervous and tossed it out the window Oh, well, that's easily remedied. We'll just work out and pick it up now But if there's nothing in it, but underwear, I he's not in front of mr. Boynton You see that was a little fib too mr. Conklin it it isn't underwear. It's something for the house You see I wanted you to be surprised, too That's right. That's what mr. Brooks told us. Yes, sir. She wants you to be surprised, too Oh, oh, well, that's different something for the house, huh? Mrs. Conklin's been talking about new curtains for the dinette. Could this be curtains? It could be for us Please mr. Conklin if you'll just hand it over I'll be eternally in your debt you are now But if it pleases you to surprise us then take it but whatever you do don't come over too early I'm not going to give mrs. Conklin my gift until after dinner. Oh, that's perfect. You'll be good and busy inside That is goodbye now The cafeteria is about to close daddy aren't you going to have lunch? I had to bite downtown Harriet when I bought your mother her birthday present Oh, what did you get her daddy a radium dial table model clock so she can see what time of night it is without waking me I took it home before I returned to school $15 I paid for that clock. She'd better like it I hope you hid it someplace where she won't find it in advance.  I hid it. All right I buried it in the little sunken toolbox out in our garden This is one present nobody could find without a geiger counter Get off that driveway walter Here's the gate to the backyard Now show us about where you got the orchid walter and I'll dig a little hole for it and put it back All right your mr. Boyden. It's over this way Bring the box. What's that box you're carrying walter this? Oh, this is the geiger counter I figured if we get away with this flower deal we can get away with borrowing the counter for one evening Oh, great. Now. I'm the co-owner of a hot geiger counter I wonder how to hatch. He is in the summertime. I'm Oh, don't worry miss brooks. We'll be through with this job in a jiffy and then we can do a little prospecting Oh, uh, stop right here mr. Boyden. I think this is pretty close to where I got the flower. All right walter Please mr. Boyden has nothing to get so excited about That wasn't me No It's a geiger counter This is where I must have stepped Miss brooks were rich South America take me away Mr. Boyden digs some more Wait a minute. I've uncovered some sort of a toolbox. What's this package? In it. Listen It's ticking It must be a time bomb A time bomb, but who would want to blow up mr. Conklin? Who wouldn't? I mean if there's uranium around here this bomb could have been planted by someone who didn't want any of us to get it That's right, or it could have been placed by some crackpot who wants to see our civilization survive Listen It's ticking louder quick. Give it to me. Here's a full watering can. This should stop it There it stopped you've done it miss brutes. Oh, you certainly have miss brooks I don't know what it is. She's done, but I'll bet I'm against it Mr. Conklin. Oh, this is one time you won't be mad at us. Miss brooks just stopped the ticking Well, she certainly did sir. She threw the whole box right into the watering can you see? It isn't making a sound Indeed it isn't But then after they're submerged in water for a while very few $15 table model clocks are capable of making any sound $15 table clock Yes, miss brooks Contained in this soggy gift wrap box is my right birthday present Well, is there any message you'd like to convey? All together gang happy birthday to you Happy birthday to you There's our miss brooks returns in just a moment, but first dream girl dream girl beautiful luster cream Tonight yes tonight show him how much lovelier your hair can look after a luster cream shampoo Luster cream world's finest shampoo No other shampoo in the world gives you k-doomits magic blend of secret ingredients plus gentle lanolin Better than a soap better than a liquid luster cream is a dainty cream shampoo Leaves hair three ways lovelier Fragrantly clean free of loose dandruff glistening with sheen soft manageable Even in hardest water luster cream lathers instantly No special rinse needed after a luster cream shampoo So gentle luster cream is wonderful even for children's hair Tonight yes tonight try luster cream shampoo Dream girl dream girl beautiful luster cream girl You owe your crowning glory to A luster cream shampoo And now once again here is our miss brooks Well when we showed mr. Conklin that his black orchid was still intact and I promised to reimburse him for the ruin clock He calmed down a bit and his complexion returned to its normal color purple After he had dismissed us I slunk back to my room and fell into a nice peaceful stupor plumber However, I awoke in the morning with a very disquieting thought The fact remained that somewhere somehow walter dentin had stepped in uranium Mr. Keller the chemistry teacher had verified that so when walter arrived to pick me up I hastened to reaffirm our partnership We are still partners aren't we walter how you bet miss brooks mr. Conklin didn't see the geiger counter at all Good now today. Let's get a hold of a sample of uranium so we'll know what we're looking for At first you'll have to give me five dollars miss brooks Five dollars we're partners aren't we you put in five and I'll put in five mr. Keller just called to tell me That's what a sample costs. Well, why should we have to buy it? Couldn't we borrow it? Hey, look miss brooks remember I told you how I got up on the table in school to fix the light bulb Yes, but what does that got to do with the uranium sample in the chem lab? That's the uranium I stepped in what sure. That's why we got to put in five dollars each to buy the school a new sample Now I've got to go to south america if only to send you a tizzi fly Actually Our miss brooks starring eve arden is produced by larry burns written by al lewis lester white and joe quillen With the music of wilbur hatch under the direction of morris carlton Mr. Boynton is played by jeff chandler mr.  And mrs. North the exciting fun fact adventures of an amateur detective And his beautiful wife tune in tuesday evening over most of these same stations And be with us again next week at the same time for another comedy episode of our miss brooks bobleman speaking This is cbs the columbia broadcast


Hello, my name is James Anderson. I'm a fitness trainer at Drew Wellness Center. I'm here today to give you some healthy holiday hints and tips on how to maintain your fitness during the holiday season. So if you're going to do a home exercise, the first thing I think is important are squats. All those squats are primarily for the legs, but it's going to comprise the quadriceps, the hamstrings, and the calves. But squats also done with proper form will engage the core. Pushups can be done against the wall, they can be done on the floor, on a chair, and you can employ different angles to get a lot more resistance in your push-ups. That can really give you a very good exercise work with multiple muscle groups in the body. After the exercise is over, to release the lactic acid, to bring the muscles and the joints and the tendons back to the proper use and function, stretching is extremely important.


The presidential candidate of the People's Democratic Party PDP, Atikubu Bubakan, said that the reputation of the country is at stake. Briefing newsmen at the World Press Conference on Thursday, Atikubu vowed to continue in the inquest of the academic records, saying there is no backing down until the Supreme Court decides. The former vice president, who had maintained silence since the release of the documents secured release of Tiananbu's education records from the CSU through a consupena against the disclosure by the president. This quest is not for or about Atikubu Bubakan. It is a quest for the true man of truth, morality, justice and accountability in our public affairs. I will only drop the fight when the court rules, in the court rules that I am right, in the court rules that he's right. So that's the end of the fight because at the moment we are the Supreme Court and there is no any harder court than the Supreme Court. Meanwhile, Kalu Kalu, the lawyer to Atikubu Bubakan, says President Bolo Tiananbu's academic documents released by the Chicago State University CSU indicated many things about the Nigerian leader. He spoke on Thursday during a press conference held by his principal, the presidential candidate of the PDP in the 2023 election in Abuja. And the documents Bolo Tiananbu submitted to INEC, he denied having dual citizenship, which means it does not belong to him. Then the same document or a deposition says that the A, Bola Atikubu, is Ahmed. But the NOS certificate Bola Ahmed Tiananbu submitted to INEC has Adekunle. I don't know where the Adekunle and the Ahmed emerge from. So on the second arm of your question of what use will it be in the Supreme Court, it is very, very clear that from the certain authorities, the Supreme Court has heard that they can accept a party to abuse fresh evidence as long as certain conditions are met. And from what transpired in the proceedings in US courts, that condition has already been met. So as we speak, our law is very clear that a party at fault cannot be allowed to enjoy the fruit of his illegality. Atikubu further called on our Nigerian leaders, including traditional and religious leaders, as well as political leaders like Pito B. and Rabiu Kwankwaso, to join in the campaign to ensure property. The released records, which came first on October 3, and the deposition showed that Tiananbu's 1979 CSU certificate he submitted to the Independent National Electrical Commission, INEC, was different from samples of the certificates the university issued to students that same year. Today, we are called upon to again, as a people, to uphold and defend the ground rules of elective government in our country. The Constitution prescribes the requirements for those who seek the highest elective office in the land. It should not take months or indeed decades for the institutions concerned to be able to do their work in establishing the credibility of any certificates presented by candidates for public office. We undertook this journey at gross cost and for important reasons. The ground rules for legitimate governance in our country need to be updated.


It's been a fantastic day. It's been a long day, but a very very enriching day. We have gone through many, many entries from different parts of the country, from different agencies, from different corporates and yes, it's been really inspiring to see so many different people doing such great work. So yes, tough day, but fantastic. So nothing succeeds like success and these people who have put in their their nominations forward know that very well and what is interesting to see is that they are looking at success from different parameters. Some of them have gone into the traditional, comfortable, traditional media format. Some people have actually challenged that, brought in a lot of digital research, data, inputs into that. Some people have taken the root of policy advocacy. Some people have brought in a marketing mix into their work. So I think it's been a little bit of everything and which is what makes it so much more enriching and exciting.


And that's my colleague Ganesh, we're both at a firm called Grandeur and we're into data visualization. This is a talk on visualizing text. It's slightly unusual and certainly a new field. Text is not something that we tend to analyze too well and it's certainly not still not audible. Text is not something we analyze too well, we're a lot better with structured data numeric and quantitative data and it's certainly not something that we know how to visualize well. Actually there aren't too many things we know how to visualize well. So this is a fairly emerging field and I'll talk about some of the advances that we made, some of the things we've learned, some examples that we've created, some examples that we've seen that are really good and hope that you'll get something out of it. My interest in text and text visualization goes back to about a decade and a half when I was first introduced to Calvin and Hobbes. Now Calvin is an amazing character. Calvin's dad is actually an even more amazing character for giving advice like this. In fact there's this subreddit which is about explain like I'm Calvin's dad. Just talking about how you give explanations exactly like Calvin's dad. Now I love giving examples from Calvin and Hobbes and when I was at BCG we were trying to create slides and every now and then I'd want to say let me pick that one slide somewhere where Calvin was talking about not understanding stuff or TV being the best medium or whatever and the trouble is you just can't find it. Do a Google search, nope. UComics which distributes Calvin and Hobbes does not have a searchable interface. So in 2001 when I got my first laptop and was commuting between Bandra and Nariman Point every day on the train, I spent all that time typing out every single strip of Calvin and Hobbes between 2001 to 2006 and I completed that task in London. That's what I used. Now to an Excel sheet where as I scroll up and down the rows I could see the different strips. In fact I can show you the Excel sheet. That's what it looks like as I go up and down. It shows me the strip and I would just now go there and say okay what's this taste it you love it blah blah blah and that was my workflow for typing this in. Took a long time but we finally got there and eventually now that the content is there it's a question of how does one search and you've got it in Excel you can copy and paste in anywhere else and you can search it but I figured a web interface would be slightly easier and created a small Calvin and Hobbes site where you can search. So for example if I want to search for, oops that's not what I want to do. If I want to search for the tracer bullet strips, okay so that's the first tracer bullet coming. That's the second one. That's the third one. Or if I want to search all the ones where snowballs were mentioned or Spacemen Spiff or Miss Wormwood you know good stuff. It went on a reddit and a few other places a number of times and one of those happy occasions it was noticed by you comics legal team and this site is now shut down. I wrote back saying look happy to offer this text feel free to use it on your site I'll build it for you if you want. No response. But the good part is this text exists and I have this corpus and I started playing around with it which marks the start of my interest in text analysis. I said what does Bill Waterson talk about? What are the kinds of words that he uses more often? And that brings us to the classic example of text visualization. If there's one sort of perfect piece of text visualization that one looks at today. It's a word cloud. You take words you plot them lay them out in a way that such that the size of the words is proportional to the frequency with which it's mentioned and you lay it out so that they just about fit so clearly Calvin Hobbes is a lot about Calvin to a good extent about Hobbes no good see mom like so on and you get a sense of what this is about if you want to get a very quick sense of what any piece of text is about this is a great way of doing it and I'll show you some examples of how you would be able to create a word cloud within a few seconds now word clouds come in many shape shapes and forms there's this guy called Jeff Clark who goes by the alias of neophomics on whose site you'll find some incredible examples so for example here's a visualization of a word cloud of words that appear on Apple's website shaped in Apple's logo word cloud doesn't have to be a homogeneous mass it doesn't have to be arbitrarily shaped you can shape it to pretty much any shape you want and the shape in itself can convey a meaning so for example this is a picture of Obama but it's actually made up of a word cloud and the words in this word cloud are the words he uses in a state of the Union speech so a lot about change and hope and so on many of these words are repeated in fact you'll also see on the site a picture of Albert Einstein in which the word Einstein is what is used in varying sizes to create this image this is a combination of data and art the shape of the picture is mostly the art part of it but to the extent that the size of the words behind it are proportional to the frequency with which that they use that's where the data part of it comes in now it's possible to create a word cloud extremely easily there's a site called wordle.net which in my opinion is one of the best word cloud sites and all it takes is let's do one thing I'm going to take the prime ministers independence Day speech in 2011 copy it go to wordle.net slash create paste this text click go run this time and there you go that's all it takes let's look at how you can play around with this I don't like this font I like cool Vettica or I like the Gothic is pretty decent I don't like this color scheme I can make it a plain black and white scheme or Indian earthy or whatever I can go for straighter edges if I like straight edges but rounder edges tend to look good you can lay it out in any a random way or half and half half horizontal half vertical or entirely vertical but usually horizontal layouts are the easiest to read and you can you can play around with the word schemes and so on it's fast and it's very tough to get this kind of a smooth beautiful layout but also you can see what he's talking about he's talking about the country a whole lot he's talking about brothers and sisters in fact he's talking about brothers and sisters a little too much probably certainly talking about the government he's talking about prizes he's talking about political he's talking about the parliament he's talking about development he's talking about people economic you don't have to read what was it 20 paragraphs to get a sense of what this is about you know what he's talking about in fact one of the partners that we had at BCG said look I don't need to read any of Abdul Kalam speeches I know what he's going to talk about he's going to talk about children he's going to talk about science he's going to talk about education you don't always need to read something to get a gist of what is being spoken about in that context and word clouds help a lot now the trouble with word clouds though is so when you take a look at this one you don't often get the context in which this is being mentioned so when you say country what is he saying about the country when he's saying brothers or sisters what is he telling his brothers and sisters to do when he says also also what so the context is something that's a little difficult and there is a technique called concordance which is popularly used to bring this about let me give you an example of a concord a piece of concordance in Calvin and Hobbes so if I want to search for let's say what does Calvin think about girls okay so Calvin thinks girls are slimy slimy slimy and the bulk of what he thinks about he certainly doesn't like them girls and associated words would be slugs and sissy and Susie which sort of rhymes and he's in fact gone as far as creating this get rid of g-r-o-s-s this club get rid of slimy girls club for well for the purpose that is fairly obvious then you can just explore this so what do you think about secret click on secret okay so the secret note secret note talks a lot about secret notes what do you think is important actually he thinks lots of things are important I'm expecting important calls doing big things you get a sense of the context of this now what if we could combine these two so if we could combine both a concordance a concordance with word cloud so now no such tool existed no such tool exists to my knowledge so we ended up having to build one this is available at s.i.p.s annan.net now I'll explain what this s.i.p. bit does but first let me demonstrate this to you so these are all the words in Calvin and Hobbes the larger the word the more often it occurs so Calvin is pretty common Calvin ball is pretty common the smaller words like biology bidding and so on are not so common you can play around this with this a little bit you can ignore the common words so those are the words that are you can ignore the infrequent words so these are the words that are mentioned fairly often you can play around the scale a little bit the scale increases scale decreases the contrast now that bears a bit of explanation now you may have heard of Amazon statistically improbable phrases they brought this they popularize this term when they were describing books they said if you wanted to find out what a book was about if you want to get the key elements of the plot you don't need to read the book we'll just give you the improbable phrases now the improbable phrases are simply those phrases that tend to occur in the book reasonably often but not as often in the English language so you just say this book has the word has the phrase let's say Spaceman's fifth 5% of the time the English language has that 0.05% of the time so that's extremely improbable phrase whereas something like good luck occurs 10% of the time here and 5% of the time in the English copper so it's not such a big deal so that's what's going on behind the scenes here the darker the word the more improbable it is in the English language the lighter the word the more probabilities so if I wanted to see what are the words that are very improbable I can just increase the contrast on this one Hobbes, Speth, Suzie these are among the more often used words that are quite improbable in the English language. Stuff like this you can play around with this and see what where that gets you the site is sip.s-anand.net and this brings together two techniques of text visualization a word cloud and a concordance where does one use this sort of a thing are there any business examples where this tends to get used actually yes and then a number of places so to give you a couple we are doing a piece of work with a bank where we took all of the text that was mentioned in their the transactions this was actually from checks. So let's take all of the text that's written in these check transactions the two or the description or whatever and put it all together and create a word cloud. So a lot of it is about cash so you pay as cash but you can also see some details around where it's going to so for instance Fab it is going to HDFC there's a bit going to the lines there's a bit going to escrow accounts you can also see the kinds of names that these checks are being written to a lot of shahs, patales this is incidentally Bombay data. So there is like but I suspect that this may be the case even otherwise a lot of payments being made to companies limited, public limited companies, LICs and so on and then you can start saying okay these are the ones that I'm going to focus on. So for instance the organization we were working with they were looking to see what are the organizations they need to partner with to minimize their payment costs so we made a simple list and said okay those are your top 10 payments you need to worry about LIC payments, MTNL payments and BSES payments between these three they cover the vast majority of where people write checks to and this is despite them not being able to track the various accounts to which this check is being sent to. So it helps summarize what is available in an in an unstructured form in a very different example. Let's take has geek the has geek job board if you were to for those of you are not aware of the has geek job board has a job board where people can post jobs and I pulled out the description of all of the jobs that were posted since last August. Those are the words that people are looking for in the cities lots of experience you know if you're a fresher you may as well not apply Bangalore that's where everything happens in fact you'd be hard-pressed to find many other cities Mumbai to a certain extent but I mean just look at the contrast between these you better know JavaScript well okay actually next to experience you should have lots of knowledge and skills and be good at teamwork hardcore web developer or web designer one or the other now let's sorry feel free to ask questions as we go along by the way is it possible to use a phrase or an Ngram to do this yes and I'll show you an example where we do that the trouble with a phrase or an Ngram is differentiating between multiple ends. So how do I know whether a word is so let's say I have call center now I have that has two words call center and the phrase call center. So how do I know when I use call independently and when I use call center the phrase together tough problem I don't have the answer some people do have techniques that I'm not aware of but techniques exist but a simple way of doing it is to say look I'm going to take not just every single word but I'm going to take the words and by grams and trigrams and so on and I'll show you an example where we did unigrams by grams trigrams and walk through that yes the site a question is what are the site visual dot L y do does it do something similar not quite they're more an aggregator of visualizations. So they you send them a visualization they'll show you what it's about. Is it possible to figure out if word like call center is more learned by using the question is can't we use other corpus like the Google search queries or some of the corporate to find out if a phrase occurs more often than not absolutely you don't even need to go to a third party corpus you can just look at it within your own data set and try and see if for instance a word is used like call and it is invariably associated with call center immediately afterwards you may as well knock off that word which is what I've used I mean it's just a simple algorithm if a word is used with another word more than 50% of the time then just knock off the individual word. It's a very very crude heuristic but it works. Well since we're talking about this one I'm going to show you the combined version of this so let's increase let's ignore the common English words so what are people looking for? Primarily they're looking for people at Bangalore doing analytics what do they want in analytics? They want data and analytics, web analytics, data analytics, web analytics so that's pretty much it data analytics and web analytics. What do they want with Facebook? They want to launch Facebook and Twitter presence Facebook connect Facebook connect Facebook campaigns what do they want to do with optimization? It's SEM optimization performance optimization search engine optimization performance optimization just two kinds of optimizations that people want search engine and performance optimization. You get a sense of what people are looking for just by playing around with this kind of data set. Another way of using this is we took survey data where services organization had asked their customers to fill out a series of questions and asked them to be rated on a scale of one to five one is bad five is good. I said okay let's take all of the good ratings together and see what words are common there and that's the green stuff on top and what are all the bad ratings put them together at the bottom and see what the problem is. So clearly this organization is great from a flexibility perspective for good teamwork decent from a customer support perspective not bad at communication but the trouble is technical quality. I don't know what this is communication communication occurs in both places so there are some people that think communication is good communications some people think communication is bad and without having to go through the hundreds of pages of comments you get a sense of where we're doing well where we're not doing well those are some examples where it can be applied you know in business in the business world this is an example where we took in grams in my previous life we were looking at intranet search results and said let's see what are the words that are searched most often so the word that was searched more often are you able to see this the word searched most often was management followed by case followed by value blah blah blah and the question is what is the context in which these words are being searched for so let's take management now management is primarily being searched from the context of change management 8% of the time program management 6% of the time performance management blah blah blah so I get an idea of what this is about let's look at what we so when somebody search for portfolio click on that what does that mean portfolio is mainly about portfolio management so this is one of those cases where if somebody is looking at the at two words portfolio and portfolio management you may as well knock off portfolio as a standalone because almost half the time it's being associated with portfolio management but it's also being associated to certain extent with portfolio rationalization portfolio analysis and so on these are ways of exploring this data set which is search data set in a somewhat semi-structured fashion but one of the things that is missing here is now while I can get the context at any point I can't do deep accelerations so for example I can say okay let's start with application see how application is used within application it's being used a lot with mobile so click on mobile see how it's being used etc but it would be nice to have some kind of a network diagram where sort of like Google's search interface that used to exist the search we where you click on a word it tells you the related concepts you click on that you search for the related concepts and so on obviously I couldn't resist doing this with Calvin and Hobbes so this is what it looks like let me zoom in so if you start with Calvin the closest associated words the words that are immediately next to it are Calvin bed Calvin Calvin Calvin stop Calvin doing Calvin Hobbes Calvin mom Hobbes is a lot closer just come are a lot closer so let me click on some of these words so let's take see doing doing what Calvin's mostly doing homework or not rather Calvin bed Calvin has to go to bed tonight Calvin here let here I don't know what that is Calvin in time there's a lot around time so bed time clearly time machine Calvin plays around a lot with the time machine what about dad what does dad do dad said something about Calvin not as interesting Calvin's work with none of these have any interesting words mom is fairly sure about number of things mom just said something or the other and this is another way of playing around with text data so once you know the relationships between paths of words and you know what's closer what's further away you can start exploring concepts you can start exploring search terms you can start exploring pretty much anything that follows the structure of a network and see where that takes you let me show you some examples from let me show you some examples that have been used elsewhere so this for instance is a Twitter stream graph Twitter stream graph is you search for a phrase in this particular case you search for the phrase data visualization and it shows you a timeline where different words are depicted as an area graph so this period of time there were lots of mentions of words associated with data visualization the guardian was talking a lot about data visualization team arcade retro these were associated a lot this particular time lot talking about lot of mention about Twitter I presume that's Twitter Inc lot of mention about social networks and that's another way of seeing what is the air by the flow of some of the words over time in the context of a specific word this is available on Jeff Clark's site in your Formics and you can try out various words it tends to fail every now and then but you might get lucky with this another is a trends map where you can take the same words and plot it instead of on a timeline plot it geographically so what are the words that are trending in specific locations so for example in India when I took the screenshot the central regions of India we're talking a lot about Cargill and Revenue and Modi Amitabh was fairly popular in Mumbai isn't he always and furniture Muslims all of this riots those were being mentioned of fabric in south and this is a real time feed that you can check out on trends map that doesn't look too good let's go on to another example yeah that's a visualization of the sentiment of the Bible by the open Bible dot info website now sentiment analysis is for those of you familiar with text analysis a very hot topic and the crux of it is to take a phrase and determine whether you can whether it's a positive sentiment whether say for example somebody tweeting about you likes you or doesn't like you somebody tweeting about a topic likes a topic or doesn't like a topic and there are various varying degrees of accuracy in sentiment analysis I'm not going to go into the content or the sort of the technique of the analysis let's just assume that there are ways of identifying the sentiment of a given phrase somewhat accurately and what this does is starts off with the the Old Testament moves on to the New Testament so the Bible starts off on a slightly positive note becomes increasingly negative for a while slight respite there fairly negative and then things look good so after the time of Moses things are good which we sort of know and around the time of Joshua things are good but around the time between Joshua and David there is a bit of strife and during the time of monarchy things are mostly good but then it starts dipping and goes all the way up to here at which point starting with Jesus there's the New Testament and that's around the time when there was a lot of resistance to what he was talking about formation of the early church and so on now this sort of a visualization actually I should take a brief detour I want to talk about this whole concept of circular visualizations I mean they look really neat and classy not quite related to text but I do want to mention that we were playing around with audio we took a bunch of songs and said let's see if we can plot songs in a similar way so the the way this is plotted is let's take Eric Clapton's wonderful tonight song starts here these are the low beats these are the high beats so that's the spectrum of the song and the the darker the color on the boundary the the deeper the beats the brighter the color on the inside the higher the treble and all the the frequencies in between are shown here so now wonderful tonight is a relatively uniform song there are too many changes whereas if you look at Queen we will rock you you can see where the pattern is completely different the duration of the song is depicted by the length of the arc in this particular case just want to show you that circular with visualizations can actually compress a fabric of information into a relatively compact space another way of looking at data is on a time series but this is shown in a somewhat different way this is a calendar that shows the sentiment of the Calvin and Hobbes published on that day so it started on the 17th of November goes on to December January and so on this is a long friend but he starts off on a happy note not so happy the next couple of days where is the fabric but you'll notice that he's extremely neutral on Sundays all of the Sunday strips which are the color strips absolutely no strong sentiments one way or the other and that was a relatively happy time that more or less but it starts turning darker one might want to test if Bill Watterson was a bad Monday person whether his Monday comics tend to be a lot more negative than usual that's I'll show you a slightly longer version of this so that's that's the point actually so maybe he was being very neutral on Saturdays rather than Sundays never know no but he did have the habit of writing fairly early so it may not be reflection of his mood versus the day he wrote it on but it certainly is a reflection of the format because the format on Sundays is a color largest strip than it is on any other day and you can get a sense of what the pattern looks like over time see he starts off being reasonably polarized there's heavy reds and greens to start with but over time it tends to tone down and in the middle so in this region he's not that opinionated there was a stretch where he was fairly okay and then towards the end it starts picking up again okay so there are many apis that sorry the question was how what are the how do you figure out if the emotion is positive or negative or how do you figure out the sentiment there are enough apis to do that in fact at the end of the stock or sometimes we have time I'll show you the code that was used to generate this I generated this this morning and it doesn't take too long to create something like this another way of looking at data is this one so this was done for the US presidential elections on any given day you show couple of bars so that sort of represents the day and the reds and the blues indicate whether they are Democrat or whether okay sorry next step back this is about what are the news sentiments about either party or either candidate now there are six combinations so there are you know firstly the reds are the mentions about the Republicans the blues are the mentions about the Democrats if it's got blocks in between then it means that it's a mention about the party if it's a straight block like this one it's a mention about the candidate McCain in this particular case and if it's darker then it's talking about a larger number of fees that are talking about the same topic so you take news topics aggregate them and say I have 20 news items talking about the same topic I have five news items talking about the same topic the 20 news items one becomes darker the five news items becomes lighter and you plot this and you get a pattern like this for instance this was on October 10th where Phelan was accused of abusing power and I don't quite know the context of this but there was apparently a large number of media mentions and you can see that the reds are generally below the line the further below the line the more negative it is so here is a case where it's a position that indicates the sentiment not the color because the color is being used for the party and consistently you'll find the reds below especially the dark reds barring one exception where McCain said that no that intervention was not unlawful and that garnered them a bit of good press but otherwise consistently the parties been doing negative this is in fact an example of an actual analysis that was used by the party created by the University of Constance in Germany another way of looking at content is if you take the state of the union speech by Obama in 2010 versus 2011 the words are sized the bubbles are sized based on how often the the words on the left where words he used more often in 2010 the words on the right he used more often in 2011 words in between where use in both instances in roughly the proportion of their location so you can see that 2010 is largely about financial bill problems million pay all of the financial crisis issues whereas 2011 is about the future best success high idea education research technology clearly an election year I'll walk you through some or rather I'll ask my colleague Ganesh to walk you through some examples that we've done in somewhat unusual spaces thanks madam we'll talk about some interesting case studies from the Indian context I'll stay away from Calvin and Hobbes not my cup of tea we wanted to take up some Indian epic and visualize large volumes of text and Mahabharata was an ideal candidate for this because it has over 1.8 million words spread across 18 chapters and over 500 sub chapters so we read we actually scanned the complete text of Mahabharata in English and create some visualizations on top of it we show a sample of it here the first one is a simple occurrence visualization this shows when each of the characters of Mahabharata had mentions in each of the chapters so we have 18 chapters and each of the boxes each of the boxes that you see here the length of the boxes proportional to the volume of text in that sub chapter if I click on any one particular character it shows in which chapter the character was mentioned so Deviani is again not a central character in the plot sub plot or a sub story there are hundreds of characters like this and hundreds of stories which happen in the Mahabharata apart from the central one this this tool actually helps us to interactively explore where each characters appear and what is the kind of interaction between each of them for instance we could see where Karna and Kunti were separated and where they got united again and stuff like that so this the position is relative to the mention whether it's mentioned starting the text or at the end of chapter so it's again relative to the specific mention so this is one analysis and then we looked at network diagram to see the closeness of different characters because the first visualization just talks about the occurrence whereas we wanted to see how closely the characters are to each other so we took up every pair of character in Mahabharata and we looked at how many words separate each of the characters so it could be five words 50 words of 500 words so the average degree of words of separation between two characters was taken and computed for the complete text and we created a network diagram based on that so each of the characters are shown and then the position in the network and the connection is based on how close each of the characters are so we can see that Yudhishthira is again the central character in the plot and there are other people around him and Bhima and Karna are also fairly well networked if I may use and there are a lot of other characters like Nakla Sahadeva and so many other characters which are interacting with more with certain specific characters but on the periphery of the plot and for instance Gandhari apart from Dhritrestra she is quite close to Vidhara and also to Kunti so this brings out a lot of interesting stories and analysis possible so this again is an interactive version which is available on our website can play around with it and see what is the strength of the network and how it moves around so sorry I didn't get the question you're asking yeah it's actually the mentions the number of words it is the two characters are separated it could be interaction, direct interaction between the characters or it could be they just spaced they're talking to different characters but spaced apart so the closest we could do was look at the number of words which separate the characters which is an approximation for the closings of the characters yeah this can't hear you yeah, excuse me sorry the question was how do you handle people having different names so for instance Arjuna has a hundred names in the text to the extent that we knew the names we just merge them all into the same name Arjuna Krishna has even more names and to the extent that we could you know we managed you know Krishna, Janata, Nagavinda the whole works we left out some of the edge cases some you know domain knowledge does help I'll move on to the next one actually we're running out of time we did an analysis of all the tweets in India so we took up one week worth of geocorded tweets from India there were about 80,000 tweets so this again includes only the geocorded tweets and so we did a document comparison analysis so similar to the other one that you saw the US case study so here we have shown a bubble chart wherein the size of the bubble is proportional to the number of mentions of that particular word and separated into two sections the words by people with low followers whereas the words by people with more number of followers so certain things which clearly come out are people with high followers tend to use a lot of hashtags and they tend to be relatively if I may use the word more polite with good mornings, good day, thanks and so on and people with low followers tend to use words no traffic and high like extremely more the correlation between the low followers and the words they use these three words is very high so there are other contrast analysis you've done again in the interest of time I'm skipping those they are available in our blog so I'll move on to the next one so this looks at which names score better marks so this is interesting enough favorite data set so this data is actually from Tamil Nadu board exams the 10th and 12th standard board exams has records of over 10 lakh students and for more than 5 years of past 5 years of data so what we've done here is this particular analysis we have taken up interactive pre-map to show all the or rather the top 5000 names the top 5000 names and then the boxes show the number of occurrence of that particular name obviously the bigger boxes mean the names are more popular the smaller boxes the reverse and the color indicates the score dark blue means higher marks and closer to white is blue certain interesting things come out if I look at high marks there are certain specific kinds of names which come up Shweta, Shriya and more urban city kind of names come up here and apart from that we also saw lot of Agarwal, Guptas, Jains and lot of North Indian names coming here this is from Tamil Nadu and low marks again you see some big boxes and many of the names are again more traditional names like Murugesan, Ayyappan and so on another interesting observation from this is that some of the more common names are have bigger boxes and the marks are averaged out whereas the less common names either have very high scores or very low scores obviously because the averaging effect impacts it so this is one of the analysis we could do on this it doesn't that's right yeah we haven't factored that in this another visualization we've got that does it but the rough rule of thumb is in terms of the by and large the polarized marks have a lesser standard deviation the ones in the middle have higher standard deviation I'll just quickly wrap up the one point that we wanted to convey is text which is generally considered unstructured has a far bit of metadata that you can extract out of it if you just try hard enough there's one thing that we want you to remember it is look hard within text you'll find weird structures like similarity, associated metadata and so on from which you can pull out the data and then visualize it last one second plug about us our organization is called Gramna you can find out more about some of our work including some of these examples at gramna.com we are into data visualization and you can reach us at this location I guess we are out of time so we probably won't take questions since we just have we have lunch right after this we have time for a couple of questions if you have any otherwise yeah sorry go on the question is which platform is it made on python like in the example of Mahabharata the noun that you are looking for were you using any parser or it was just your own knowledge in a sentence if you are looking like if you are using a Stanford parser you are looking for the noun then you can have all the combinations of nouns so did you use those parsers or something let me just rephrase that question to how do we figure out the names no we didn't really we didn't need a parser it actually turned out to be simple enough to get it down to 90% accuracy by saying you know by just looking at the capitalized words we said take all the words that begin with the capital letter and ignore those words that are already in the dictionary that gets you to 90% accuracy and then we just did a manual filtering sorry that wasn't the question yes absolutely it turned out that in this particular case it was mostly names sorry the comment was that might have been places that might have been names so how do you know did we do anything smarter than that it turns out it just wasn't required in this particular instance I am not saying that a parser is not a good thing in fact a parser is a phenomenal thing it's just that there are occasions when sometimes a simple heuristic works reasonably well too and we just got lucky here my question is related to my experience of text processing which two typical problems comes up one is that time like sometimes like if you see the text of Mahabharata many things are discussed in context of past or their background flashback so time goes like if you interpret with that time it goes wrong second bigger problem I face actually we face try to come up was like U, I these words were actually not the words but they were actually representing something else and how we deal with these kind of problems so the question is one Mahabharata talks about different periods of time how do we handle that secondly words like U, V, I they have different meanings in different contexts how do we handle that in this particular example we just did and again given that this is a talk on text visualization I don't want to go into any of the techniques around text analysis if you will but let me just say that it's a pretty tough problem you mentioned about sentiment analysis do you have any open source APIs or something can you if you tell that the question was do we have any open source API on sentiment analysis no but a whole bunch of other people do in fact let me see if I can find the code that we used to do this analysis the one we used was viral heat so viral heat provides an API where you can just pass in a phrase and you will get the sentiment against it this was the first one that early this morning I googled and found you will find hundreds of others Python's NLTK has some parsers which will help you extract the meaningful text out of it to send to these or any other APIs and there are a number of others as well one last question so the question was how scalable is NLTK it is a bit slow but that's the nature of the algorithms themselves to the extent that you can cache it do some of the processing offline and reuse those results you are fine I haven't seen too many analysis of text data at a very large scale so we haven't really encountered this problem the quick answer to that question is NLTK scalable is probably not but don't know of a better alternative in Python great presentation so maybe one thing you may want to kind of share with the group is what are all the different tools that you use besides Python, NLTK and the viral heap that you talked about just now so your question was what are the tools that we might want various tools that you recommend people use the hidden tool behind half of these analysis is actually Excel take the data find a set of keywords do a find equal to find a particular keyword see if it exists or not that's what led to the visualizations a bunch of visualizations the whole Calvin and Hobbes was typed in Excel so I would add Excel to the portfolio and the reason I'm saying that is because I'm assuming that there would be a reasonable number of non-programmers in this room as well for example if you wanted to create a word cloud the way I would do it is type a bunch of and a lot of people want to mock up word clouds you want to create it for marketing purposes open up Excel type a bunch of words next to it type I'm not going to show it to you, we don't have time type of formula that says equal to R-E-P-T the word comma 10 that will repeat the word 10 times repeat the next word 5 times and so you can have a bunch of words in the frequency that you want copy and paste that text into Wordle and you're done so for the non-programmer I would say between Excel and Wordle you've covered the bulk of text visualisation that you can probably hope to do in the near future in a reliable fashion beyond that other than I wouldn't necessarily say Python, NLTK that's not the only toolset that one can use there are a number of APIs that are emerging the thing is the state of this is not so stable today that I would be able to suggest something concrete but apart from Python and NLTK regular expressions are your best friend thank you Ajay sorry, thank you Anand and Girish thanks everyone we'll break for lunch now and be back at two


I commit to learn more about how I can have a shipmate in trouble. No more, I didn't know what to do. I commit to intervene early, more often, and before a problem becomes bigger. No more, he's a smart guy. He can take care of himself. I commit to notice, to investigate, and to recruit friends to help in a sticky situation. No more, I don't want to get involved. I commit to make it my personal responsibility to be the first person to help a shipmate in need. No more, let someone else deal with it. I commit to stop making excuses. No more, it's not my problem.  Will you?