Sentiment Analysis and Emotion Classification using Machine Learning Techniques for Nagamese Language -- A Low-resource Language

Fuente: arXiv
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Auteurs principaux: Morang, Ekha, Ngullie, Surhoni A., Longkumer, Sashienla, Angami, Teisovi
Format: Preprint
Publié: 2025
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author Morang, Ekha
Ngullie, Surhoni A.
Longkumer, Sashienla
Angami, Teisovi
author_facet Morang, Ekha
Ngullie, Surhoni A.
Longkumer, Sashienla
Angami, Teisovi
contents The Nagamese language, a.k.a Naga Pidgin, is an Assamese-lexified creole language developed primarily as a means of communication in trade between the people from Nagaland and people from Assam in the north-east India. Substantial amount of work in sentiment analysis has been done for resource-rich languages like English, Hindi, etc. However, no work has been done in Nagamese language. To the best of our knowledge, this is the first attempt on sentiment analysis and emotion classification for the Nagamese Language. The aim of this work is to detect sentiments in terms of polarity (positive, negative and neutral) and basic emotions contained in textual content of Nagamese language. We build sentiment polarity lexicon of 1,195 nagamese words and use these to build features along with additional features for supervised machine learning techniques using Na"ive Bayes and Support Vector Machines. Keywords: Nagamese, NLP, sentiment analysis, machine learning
format Preprint
id arxiv_https___arxiv_org_abs_2512_01256
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Sentiment Analysis and Emotion Classification using Machine Learning Techniques for Nagamese Language -- A Low-resource Language
Morang, Ekha
Ngullie, Surhoni A.
Longkumer, Sashienla
Angami, Teisovi
Computation and Language
Artificial Intelligence
The Nagamese language, a.k.a Naga Pidgin, is an Assamese-lexified creole language developed primarily as a means of communication in trade between the people from Nagaland and people from Assam in the north-east India. Substantial amount of work in sentiment analysis has been done for resource-rich languages like English, Hindi, etc. However, no work has been done in Nagamese language. To the best of our knowledge, this is the first attempt on sentiment analysis and emotion classification for the Nagamese Language. The aim of this work is to detect sentiments in terms of polarity (positive, negative and neutral) and basic emotions contained in textual content of Nagamese language. We build sentiment polarity lexicon of 1,195 nagamese words and use these to build features along with additional features for supervised machine learning techniques using Na"ive Bayes and Support Vector Machines. Keywords: Nagamese, NLP, sentiment analysis, machine learning
title Sentiment Analysis and Emotion Classification using Machine Learning Techniques for Nagamese Language -- A Low-resource Language
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2512.01256