Sentiment Analysis of Vulnerable Data in Social Networking

  • Chitra Prabha.R, Nandini.S, Gayathri.R

Abstract

Social network has seen the vital growth in recent years. Any information posted on social media goes viral among the people regardless of the originality of the source. Classifying the posts and determining whether or not to trust the post has become very important. In this context, Current System focusses on user mentions-links between users who are created by answering, mentioning and posting their texts (dynamically or unintentionally) in our walls. Nevertheless, the post hits multiple users until it is proven to have been false. Thus, the people listed in the article can get defamed and fake news can virally spread in social media. In the proposed method, after the user finishes typing, sentiment analysis is carried out on the postal data, keywords are compared to web surf results which verify news pages and related official pages. Based on its true value, the system decides if the post option should be enabled or not. In this method the post hits no users if expected to be incorrect and thus social media credibility is improved considerably, thus providing users of social media with a better experience.

Keywords: Social creation, Web surf, True value calculation.

Published
2020-06-06
How to Cite
Chitra Prabha.R, Nandini.S, Gayathri.R. (2020). Sentiment Analysis of Vulnerable Data in Social Networking. International Journal of Advanced Science and Technology, 29(04), 6251 - 6255. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/27311