Social Networks Personality Googler

It is very valuable to study and enhance today's changing dynamics of social interactions. In particular, important insights can be derived from lexical sentiment analysis of the posts on the Social Networking Site - Facebook. These results can then be used to evaluate the overall emotional level of a human. Sentiment analysis traditionally emphasizes on classification of Web comments into positive, neutral, and negative categories. This paper“Social Networks Personality Googler” goes beyond sentiment classification by focusing on FFM algorithm that can identify the emotion of individuals through their Facebook posts. This can then help sociologists understand both the overall sentiment scope of a community as well as the drivers behind the sentiment. Our project hence, concentrates on analyzing the personality of an individual based on his Facebook posts. This can be made more effective by introducing “Stemming algorithm” as a part to process the posts.