{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/team-phoenix-at-wassa-2021-emotion-analysis","title":"Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language Models","arxiv_id":"2103.06057","date":"2021-03-10","proceeding":"EACL (WASSA) 2021 4","authors":["Yash Butala","Kanishk Singh","Adarsh Kumar","Shrey Shrivastava"],"abstract":"Emotion is fundamental to humanity. The ability to perceive, understand and respond to social interactions in a human-like manner is one of the most desired capabilities in artificial agents, particularly in social-media bots. Over the past few years, computational understanding and detection of emotional aspects in language have been vital in advancing human-computer interaction. The WASSA Shared Task 2021 released a dataset of news-stories across two tracks, Track-1 for Empathy and Distress Prediction and Track-2 for Multi-Dimension Emotion prediction at the essay-level. We describe our system entry for the WASSA 2021 Shared Task (for both Track-1 and Track-2), where we leveraged the information from Pre-trained language models for Track-specific Tasks. Our proposed models achieved an Average Pearson Score of 0.417 and a Macro-F1 Score of 0.502 in Track 1 and Track 2, respectively. In the Shared Task leaderboard, we secured 4th rank in Track 1 and 2nd rank in Track 2.","url_abs":"https://arxiv.org/abs/2103.06057v1","url_pdf":"https://arxiv.org/pdf/2103.06057v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"team-phoenix-at-wassa-2021-emotion-analysis","repo_url":"https://github.com/yashbutala/WASSA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}