Findings of shared task on Sentiment Analysis and Homophobia Detection of YouTube Comments in Code-Mixed Dravidian Languages
Proceedings of the 14th Annual Meeting of the Forum for Information Retrieval Evaluation(2022)
摘要
We present an overview of sentiment analysis and homophobia detection of YouTube comments in code-mixed Dravidian languages in this paper. We provide the details of this task and the submitted systems for the tasks. We introduce two studies: task A for detecting sentiment analysis and task B on homophobia detection, which is organized by the FIRE 2022. A total of 95 participants registered for the shared task, 13 teams finally submitted their results for task-A a, and 10 teams submitted their results for task B. The teams explored tasks A and B using traditional machine learning and deep learning models. Most of the benchmark systems have been analyzed by participants capable of handling code-mixed scenarios in Dravidian languages.
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