Sentimental Analysis On Social Media

Authors: Mr. Tambe Nitin A., Mr. Satpute Onkar G., Ms. Wakchaure Gauri V., Ms. Patole Sakshi S., Mr. S.M Rokade

Country: India

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Abstract: This project introduces a web application aimed at analysing Facebook posts by conducting sentiment analysis on their descriptions. Leveraging Natural Language Processing (NLP) techniques, the application scrutinizes the textual content of posts to ascertain their emotional tone. Through sentiment analysis, posts are classified into three primary categories: Normal, Positive, or Negative, based on the sentiments conveyed in their descriptions. The application offers users valuable insights into the prevailing sentiments expressed within the Facebook community. By categorizing posts according to sentiment, users can better understand the emotional landscape of their social network, identifying trends, patterns, and potentially significant discussions. Moreover, this tool enables users to efficiently navigate through vast amounts of content, prioritizing posts based on sentiment for further attention or action. Ultimately, the web application serves as a valuable resource for individuals, organizations, and researchers seeking to gain deeper insights into the sentiments prevalent within the Facebook ecosystem, facilitating informed decision-making and fostering more meaningful engagement within the online community.

Keywords: 1. Web application 2. Sentiment analysis 3. Facebook posts 4. Natural Language Processing (NLP) 5. Emotional tone 6. Normal, Positive, Negative categories 7. Insights 8. Social network 9. Trends 10. Patterns 11. Decision- making 12. Engagement 13. Research 14. Textual content 15. Emotional landscape.

Paper Id: 230663

Published On: 2024-05-25

Published In: Volume 12, Issue 3, May-June 2024

Cite This: Sentimental Analysis On Social Media - Mr. Tambe Nitin A., Mr. Satpute Onkar G., Ms. Wakchaure Gauri V., Ms. Patole Sakshi S., Mr. S.M Rokade - IJIRMPS Volume 12, Issue 3, May-June 2024.

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