Sentiment Based Recommendation System for Psychological Patterns of Social Media Users


Authors : Dolly Tejwani, Prachi Dabhade, Vaidehi Satpute, Shital Gopatwad, Prof. Shrikant Kokate

Volume/Issue : Volume 2 - 2017, Issue 12 - December

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/tPhncZ

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

Sentiment analysis is one of the fastest growing research areas in computer science. This paper deals with the recommendation based on the sentiment analysis of text, specially the posts that are posted by the users of the social media. The sentiment found within the posts and comments provide useful indicators for many different purposes as people nowadays tend to express their emotions on social media publicly. In existing systems sentiment analysis is done using lexicon based approach, rule based approach or by using machine learning algorithms In this proposed system, sentiment analysis will be done using text mining algorithms and depending on the intensity of the sentiment the user will be recommended with positive quotes and images to lift up their moods.

Keywords : Sentiment Analysis, Text Mining, Recommendation System, Social Media, K-Means, Apriori.

CALL FOR PAPERS


Paper Submission Last Date
30 - April - 2021

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe