Using ChatGPT to Build Indian Multilingual Sentiment Analysis

EasyChair Preprint 14495

Abstract

India, with its vast linguistic diversity, poses a unique challenge for sentiment analysis. This paper explores the use of ChatGPT, a state-of-the-art language model, to develop a sentiment analysis system that caters to multiple Indian languages. We discuss the intricacies of building a multilingual sentiment analysis system, including data collection, preprocessing, model training, and evaluation. By leveraging ChatGPT's capabilities, we aim to create a robust system capable of accurately assessing sentiments across various Indian languages. This paper provides an in-depth analysis of the system's construction and its performance, offering insights into its potential applications and future enhancements.

Keyphrases: ChatGPT, Sentiment Analysis, multilingual

@booklet{EasyChair:14495,
  author    = {Sarah Zhao},
  title     = {Using ChatGPT to Build Indian Multilingual Sentiment Analysis},
  howpublished = {EasyChair Preprint 14495},
  year      = {EasyChair, 2024}}