IRLab@ IITBHU@ Dravidian-CodeMix-FIRE2020: Sentiment Analysis for Dravidian Languages in Code-Mixed Text

Supriya Chanda, Sukomal Pal
September, 2020
PDF Cite Project Slides DOI
Image credit: Unsplash

Abstract

This paper describes the IRlab@IITBHU system for the Dravidian-CodeMix - FIRE 2020 Sentiment Analysis for Dravidian Languages pairs Tamil-English (TA-EN) and Malayalam-English (ML-EN) in Code-Mixed text. We submitted three models for sentiment analysis of code-mixed TA-EN and MA-EN datasets. Run-1 was obtained from the BERT and Logistic regression classifier, Run-2 used the DistilBERT and Logistic regression classifier, and Run-3 used the fastText model for producing the results. Run-3 outperformed Run-1 and Run-2 for both the datasets. We obtained an F1-score of 0.58, rank 8/14 in TA-EN language pair and for ML-EN, an F1-score of 0.63 with rank 11/15.

Type
Preprint
Publication
Forum for Information Retrieval Evaluation
Click the Cite button above to demo the feature to enable visitors to import publication metadata into their reference management software.
Create your slides in Markdown - click the Slides button to check out the example.

#Supplementary notes can be added here, including code, math, and images.

cmsa
Supriya Chanda
Supriya Chanda
Research Scholar (2018-2024)

Supriya Chanda (pronounced as Supriyo), completed his Ph.D in the Department of Computer Science and Engineering, IIT (BHU), Varanasi. He did his research under the guidance of Dr. Sukomal Pal at the Information retrieval lab.