Multi-Class Sentiment Analysis of Twitter Data Using Bert-Based Model

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ID: 312087
2025
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Abstract
Modern world is a world of social media. X formerly known as Twitter is one of the leading social media platform that represents the public opinions from across the globe on every walk of life. These opinions are not just short texts but represent the sentiments of the public. The sentimental analysis of this large scale text data give insightful information to organizations, researchers, policy makers, and government institutes. Therefore, this work proposed a BERT (Bidirectional Encoder Representations from Transformers)-based sentiment analysis model. The model classifies the X (Twitter) text or tweets as positive, negative or neutral by analyzing the text data. The proposed model is evaluated on accuracy, precision, recall and F1 score. The experiment results showed that the proposed model yielded promising performance against all sentiment classes.  
Reference Key
imported_1776679613_69e5fabd43f58 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Dr. Jahanzeb Jahan
Journal Social Sciences & Humanity Research Review
Year 2025
DOI
10.63468/sshrr.266
URL
https://sshrr.online/index.php/4/article/view/424
Keywords Keywords not found

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