Did that happen? Predicting Social Media Posts that are Indicative of what happened in a scene: A case study of a TV show.

While popular Television (TV) shows are airing, some users interested in these shows publish social media posts about the show. Analyzing social media posts related to a TV show can be beneficial for gaining insights about what happened during scenes of the show. This is a challenging task partly because a significant number of social media posts associated with a TV show or event may not clearly describe what happened during the event. In this work, we do the following: (a) collect social media (Twitter) posts associated with a TV show, Game of Thrones, (b) identify the various scenes of the TV show, (c) for each scene, we annotate the social media posts (published during the time period of the scene) that are indicative of what transpired during the scene, and (d) we propose a method to predict the indicative social media posts in each scene. We show that for each of the identified scenes, with high AUC's, our method can predict posts that are indicative of what happened in a scene from those that are not-indicative. Based on Twitter's policy, we will make the Tweeter ID's of the Twitter posts used for this work publicly available; also, we will make the annotations available.