IIIT Hyderabad Publications |
|||||||||
|
Towards Capturing Changes in Mood and Identifying Suicidality RiskAuthors: Sravani Boinepelli,Shivansh Subramanian,Abhijeeth Singam,Tathagata Raha,Vasudeva Varma Conference: Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology Pages: 1-6 Date: 2022-07-04 Report no: IIIT/TR/2022/9 AbstractThis paper describes our systems for CLPsych’s 2022 Shared Task1 . Subtask A involves capturing moments of change in an individual’s mood over time, while Subtask B asked us to identify the suicidality risk of a user. We explore multiple machine learning and deep learning methods for the same, taking real-life applicability into account while considering the design of the architecture. Our team, IIITH, achieved top results in different categories for both subtasks. Task A was evaluated on a post-level (using macro averaged F1) and on a window-based timeline level (using macro-averaged precision and recall). We scored a post-level F1 of 0.520 and ranked second with a timeline-level recall of 0.646. Task B was a user-level task where we also came in second with a micro F1 of 0.520 and scored third place on the leaderboard with a macro F1 of 0.380. Full paper: pdf Centre for Language Technologies Research Centre |
||||||||
Copyright © 2009 - IIIT Hyderabad. All Rights Reserved. |