Design and Development of a Model for Sentiment Analysis on Face-book Posts

Abstract

Social media websites like Twitter, Facebook etc. are a major hub for users to express their opinions online. Sentiment is defined as a thought influenced by or proceeding from feeling or emotion. Sentiment analysis which is also called opinion mining, involves in building a system to collect and examine opinions about the product made in blog posts, comments, or reviews. Sentiment analysis can be useful in real life. In this paper, we analyzed any person’s sentiment by using any person’s post that he/she write or share on face-book. We analyzed any person’s sentiment by viewer reply that he/she got against his/her post that he/she write/share on facebook. We proposed a new way or system by the help of our system we can analyzed any person’s sentiment. By that any person’s can know about his/her own sentiment or emotion. We take the total number of positive data (love, ha-ha, wow) and negative data (angry, sad) that he/she got against his/her post that he/she write/share on face-book, analyzed the total number of emoticon data. After analyzing the data finally we can detect any person’s sentiment or emotion is he/she Positive, Negative or Neutral.