SocialNLP EmotionGIF 2020 Challenge Overview: Predicting Reaction GIF Categories on Social Media
This addresses the problem of understanding emotional reactions on social media for NLP researchers, but it is incremental as it focuses on organizing a competition and dataset rather than advancing core methods.
The paper introduced the EmotionGIF2020 Challenge, which tackled predicting affective reactions to online texts using a novel dataset of 40K tweets labeled with reaction GIF categories, resulting in a top performance of 62.47% Recall@K by the winning team.
We present an overview of the EmotionGIF2020 Challenge, held at the 8th International Workshop on Natural Language Processing for Social Media (SocialNLP), in conjunction with ACL 2020. The challenge required predicting affective reactions to online texts, and included the EmotionGIF dataset, with tweets labeled for the reaction categories. The novel dataset included 40K tweets with their reaction GIFs. Due to the special circumstances of year 2020, two rounds of the competition were conducted. A total of 84 teams registered for the task. Of these, 25 teams success-fully submitted entries to the evaluation phase in the first round, while 13 teams participated successfully in the second round. Of the top participants, five teams presented a technical report and shared their code. The top score of the winning team using the Recall@K metric was 62.47%.