Sentiment Analysis On Social Media

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Shubham Musale; Ashwini Salunke; Avinash Kapse

Sentiment Analysis On Social Media

Authors: Shubham Musale, Ashwini Salunke, Avinash Kapse

Unique Paper ID: 163801
Volume: 10
Issue: 11
PageNo: 1997-2002

Keywords: Social Media Sentiment Analysis Natural Language Processing Machine Learning User-Generated Content Opinion Mining Social Analytics.

Abstract:
This study employs sentiment analysis techniques to evaluate public sentiment on social media platforms. By employing natural language processing and machine learning algorithms, the research aims to analyze the emotional tone and attitudes expressed in user-generated content. The investigation focuses on identifying prevalent sentiments such as positivity, negativity, or neutrality, providing valuable insights into public opinion and social trends. The findings contribute to a deeper understanding of online discourse, aiding businesses, policymakers, and researchers in making informed decisions based on the prevailing sentiment in social media discussions.

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ISSN: 2349-6002
Volume: 10
Issue: 11
PageNo: 1997-2002

Sentiment Analysis On Social Media

Available:https://ijirt.org/article?manuscript=163801

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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