Work

Research on Sentimental Analysis on Veganism

Year: 2025

Type: article

Abstract: This project introduces a sentiment analysis system developed to gauge public opinions on veganism as a social justice movement. By employing machine learning algorithms—Support Vector Classification (SVC), Logistic Regression, and K-Nearest Neighbors (KNN)—the system categorizes text data into positive, negative, or neutral sentiments. A dataset of 50,000 text entries from Kaggle was preprocessed and converted using Term Frequency-Inverse Document Frequency (TF-IDF). Comparative analysis using accuracy, precision, recall, and F1-score determined the most effective model. The scalable system supports social media monitoring and public perception research, providing insights into societal views on veganism.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15082265

Author: Omkar Singh1, Sunali Bhattacherji*2

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6967900181

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