The Forensic Algorithm on Facebook Using Natural Language Processing

These days, social media has played a significant role in daily life of all people and ages in order to communicate as well as express their thoughts and feelings. In this paper, the authors have studied user data from social media (Facebook) whose shared posts are positive, and also the negative side posts that may lead to negative affect personally or can be further extended to the community and nation level. The purposes are to identify users who have commented on the negative side that may be a lawbreaker on Computer related crime. On this which beneficial about investigation for legal proceeding and it facilitate for the police or people who take a part in the operation on law. It also contributes in the community at large to peacefulness. The effective Naïve-Bayes classifier is used in order to classify these two user groups. It significantly shows that analyzing social media data by using Naïve Bayes model presented sharing positive and negative views accurately as well as reflects satisfied results.