A Lexicon-Based Approach for Sentiment Analysis of Bodo Language

With the proliferation of digital content, it is increasingly important to understand the sentiment of the information that is being shared. Sentiment Analysis, the procedure of identifying the emotional tone of a given text, has become a crucial area of research in Natural Language Processing (NLP). However, performing sentiment analysis on Bodo language texts is challenging due to inadequate labeled data and the complexity of the language. The amount of resources and research available for Bodo language is quite limited compared to more widely spoken languages, such as English or Hindi. This study proposes a lexicon-based approach for sentiment analysis of Bodo language texts, which is a low-resource language spoken in India. For our purpose, we have considered sentences and words from various social sites and then created a Bodo sentiment lexicon through manual labeling of Bodo language words and sentences with their sentiment polarity (positive, negative, or neutral). Results from evaluating the approach on a dataset of Bodo language texts show an accuracy of 70%. This lexicon-based approach is a simple and effective method for sentiment analysis of Bodo language texts and can be used to enhance the performance of other NLP tasks such as text classification and opinion mining.