Detecting and Reasoning of Deleted Tweets before they are Posted
Hamdy Mubarak Samir Abdaljalil Azza Nassar Firoj Alam
Social media platforms empower us in several ways, from information
dissemination to consumption. While these platforms are useful in promoting
citizen journalism, public awareness etc., they have misuse potentials.
Malicious users use them to disseminate hate-speech, offensive content, rumor
etc. to gain social and political agendas or to harm individuals, entities and
organizations. Often times, general users unconsciously share information
without verifying it, or unintentionally post harmful messages. Some of such
content often get deleted either by the platform due to the violation of terms
and policies, or users themselves for different reasons, e.g., regrets. There
is a wide range of studies in characterizing, understanding and predicting
deleted content. However, studies which aims to identify the fine-grained
reasons (e.g., posts are offensive, hate speech or no identifiable reason)
behind deleted content, are limited. In this study we address this gap, by
identifying deleted tweets, particularly within the Arabic context, and
labeling them with a corresponding fine-grained disinformation category. We
then develop models that can predict the potentiality of tweets getting
deleted, as well as the potential reasons behind deletion. Such models can help
in moderating social media posts before even posting.