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Emolingual Sentiment Analysis of Tamil – English Code Mixed Text with Emoji’s

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dc.contributor.author Nizardeen, Hamza
dc.date.accessioned 2025-06-06T06:17:09Z
dc.date.available 2025-06-06T06:17:09Z
dc.date.issued 2024
dc.identifier.citation Nizardeen, Hamza (2024) Emolingual Sentiment Analysis of Tamil – English Code Mixed Text with Emoji’s . BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20200103
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2462
dc.description.abstract In today's digital landscape, content creators face numerous challenges in interpreting feedback from diverse audiences, particularly when comments are expressed in code-mixed languages such as Tamil and English, often accompanied by emojis. This research introduces a novel approach for sentiment analysis and sarcasm detection in Tamil-English code-mixed text. By integrating Bidirectional Long Short-Term Memory (BiLSTM) networks for handling code-mixed language and Convolutional Neural Networks (CNNs) for recognizing sentiment and sarcasm patterns in emojis, our approach aims to help content creators decipher the true sentiment behind multilingual comments, accurately capturing nuances conveyed through both textual and visual cues. en_US
dc.language.iso en en_US
dc.subject Sentiment Analysis en_US
dc.subject Code-mixed en_US
dc.subject Predict en_US
dc.title Emolingual Sentiment Analysis of Tamil – English Code Mixed Text with Emoji’s en_US
dc.type Thesis en_US


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