A Transformer-Driven Approach to Political Sentiment Analysis of Tamil X (Twitter) Comments
Keywords: Political Sentiment Analysis, Low-Resource Languages, Transformer, BERT
Abstract:
Social media has become an established medium of public communication and opinions on every aspect of life, but especially politics. This has resulted in a growing need for tools that can process the large amount of unstructured data that is produced on these platforms providing actionable insights in domains such as social trends and political opinion. Low-resource languages like Tamil present challenges due to limited tools and annotated data, highlighting the need for NLP focus on understudied languages. To address this, a shared task has been organized by DravidianLangTech@NAACL 2025 for political sentiment analysis for low-resource languages, with a specific focus on Tamil. In this task, we have explored several machine learning methods such as SVM, AdaBoost, GB, deep learning methods including CNN, LSTM, GRU BiLSTM, and the ensemble of different deep learning models, and transformer-based methods including mBERT, T5, XLM-R. The mBERT model performed best by achieving a macro F1 score of 0.2178 and placing our team 22nd in the rank list.
Видео A Transformer-Driven Approach to Political Sentiment Analysis of Tamil X (Twitter) Comments канала Tofayel Ahmmed
Abstract:
Social media has become an established medium of public communication and opinions on every aspect of life, but especially politics. This has resulted in a growing need for tools that can process the large amount of unstructured data that is produced on these platforms providing actionable insights in domains such as social trends and political opinion. Low-resource languages like Tamil present challenges due to limited tools and annotated data, highlighting the need for NLP focus on understudied languages. To address this, a shared task has been organized by DravidianLangTech@NAACL 2025 for political sentiment analysis for low-resource languages, with a specific focus on Tamil. In this task, we have explored several machine learning methods such as SVM, AdaBoost, GB, deep learning methods including CNN, LSTM, GRU BiLSTM, and the ensemble of different deep learning models, and transformer-based methods including mBERT, T5, XLM-R. The mBERT model performed best by achieving a macro F1 score of 0.2178 and placing our team 22nd in the rank list.
Видео A Transformer-Driven Approach to Political Sentiment Analysis of Tamil X (Twitter) Comments канала Tofayel Ahmmed
Political Sentiment Analysis Low Resource Languages Tamil NLP Transformer Models BERT mBERT Multilingual BERT Sentiment Classification DravidianLangTech NAACL 2025 NLP Shared Task CUET NLP CUET Network Society Deep Learning NLP Natural Language Processing Political Opinion Mining Multiclass Sentiment Analysis mBERT Tamil Social Media Sentiment AI for Politics Machine Learning NLP NLP Research Low Resource NLP
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19 апреля 2025 г. 20:35:51
00:07:53
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