Autores
Kanta Selam Abitte
Sidorov Grigori
Título Selam@DravidianLangTech:Sentiment Analysis of Code-Mixed Dravidian Texts using SVM Classification
Tipo Congreso
Sub-tipo Memoria
Descripción 3rd Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2023
Resumen Sentiment analysis in code-mixed text written in Dravidian languages. Specifically, Tamil-English and Tulu-English. This paper describes the system paper of the RANLP-2023 shared task. The goal of this shared task is to develop systems that accurately classify the sentiment polarity of code-mixed comments and posts. be provided with development, training, and test data sets containing code-mixed text in Tamil-English and Tulu-English. The task involves message-level polarity classification, to classify YouTube comments into positive, negative, neutral, or mixed emotions. This Code-Mix was compiled by RANLP-2023 organizers from posts on social media. We use classification techniques SVM and achieve an F1 score of 0.147 for Tamil-English and 0.518 for Tulu-English. © DravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings.
Observaciones DOI 10.26615/978-954-452-085-4_024
Lugar Varna
País Bulgaria
No. de páginas 176-179
Vol. / Cap.
Inicio 2023-09-07
Fin
ISBN/ISSN 9789544520854