代码混合德拉威语YouTube评论情感分析与同性恋恐惧症检测的共享任务研究

Proceedings of the 14th Annual Meeting of the Forum for Information Retrieval Evaluation Pub Date : 2022-12-09 DOI:10.1145/3574318.3574347

Subalalitha Chinnaudayar Navaneethakrishnan, Bharathi Raja Chakravarthi, Kogilavani Shanmugavadivel, Malliga Subramanian, Prasanna Kumar Kumaresan, Bharathi, Lavanya Sambath Kumar, Rahul Ponnusamy

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引用次数: 8

摘要

本文概述了在代码混合的德拉威语中对YouTube评论的情感分析和同性恋恐惧症检测。我们提供此任务的详细信息以及为该任务提交的系统。我们介绍了两项研究:任务A是检测情绪分析，任务B是检测同性恋恐惧症，这是由FIRE 2022组织的。共有95名参与者注册了共享任务，13个团队最终提交了任务A A的结果，10个团队提交了任务B的结果。团队使用传统的机器学习和深度学习模型探索任务A和B。大多数基准系统已经由能够处理德拉威语代码混合场景的参与者进行了分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Findings of shared task on Sentiment Analysis and Homophobia Detection of YouTube Comments in Code-Mixed Dravidian Languages

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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Proceedings of the 14th Annual Meeting of the Forum for Information Retrieval Evaluation

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