Sentiment Analysis for Code-Mixed Data Using Cellular Automata with Deep Learning Models

Author:

Elizabeth M. J.ORCID,Kommineni Avinash Krishna,Hazari RajuORCID

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Unicode 15.0 character code charts. https://unicode.org/charts/

2. Auer, P.: Code-Switching in Conversation: Language, Interaction and Identity. Routledge, Milton Park (1998)

3. Babu, Y.P., Eswari, R., Nimmi, K.: Cia_nitt@dravidian-codemix-fire2020: Malayalam-English code mixed sentiment analysis using sentence BERT and sentiment features. In: Working Notes of FIRE 2020 - Forum for Information Retrieval Evaluation, Hyderabad, India, 16–20 December 2020. CEUR Workshop Proceedings, vol. 2826, pp. 566–573. CEUR-WS.org (2020)

4. Bai, Y., Zhang, B., Chen, W., Gu, Y., Guan, T., Shi, Q.: Automatic detecting the sentiment of code-mixed text by pre-training model (2021). http://ceur-ws.org

5. Bharathi, B., Samyuktha, G.: Machine learning based approach for sentiment analysis on multilingual code mixing text. In: FIRE (Working Notes), pp. 1038–1043 (2021)

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