Did that happen? predicting social media posts that are indicative of what happened in a scene: a case study of a TV show
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Published version
Date
2022-06-20
DOI
Authors
Wijaya, Derry
Andy, Anietie
Kriz, Reno
Guntuku, Sharath Chandra
Callison-Burch, Chris
Version
Published version
OA Version
Citation
Anietie Andy, Reno Kriz, Sharath Chandra Guntuku, Derry Tanti Wijaya, and Chris Callison-Burch. 2022. Did that happen? Predicting Social Media Posts that are Indicative of what happened in a scene: A case study of a TV show. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 7209–7214, Marseille, France. European Language Resources Association. https://aclanthology.org/2022.lrec-1.781
Abstract
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 propose a method to predict social media posts (associated with scenes of a TV show) that are indicative of what transpired during the scenes of the show. We evaluate our method on social media (Twitter) posts associated with an episode of a popular TV show, Game of Thrones. 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 Twitters policy, we will make the Tweeter ID’s of the Twitter posts used for this work publicly available.
Description
License
© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0