The Facebook Analysis using Natural Language Processing (NLP)

Abstract

- Digital development in modern society and the use of Information Technology which are very useful and creative become a big part in our daily life. On the other hand, it may lead to negative affect when it is used improperly in person. User data from social media in specifically Facebook whose shared posts are positive comments and negative comments. But, the negative side comments lead to negative affect personally or can be further extended to the community and nation level when the communication or transaction is used improperly. Therefore, it is necessary 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. The problem with this issue is, without forensic evidence, many offenders in complex criminal cases are still free and may repeat offending against the laws and harm the others. On the other side, A problem of children/ person being exposed to pornographic web sites on the internet has led to their safety issues. To prevent the children/person from these inappropriate materials, an effective web filtering system is essential. Therefore, the proposed system explores to classify the shared posts in to positive, negative comments, identifies particular user who have commented on the negative side on the online social networking specifically on the facebook and also handles the web filtering technique to filter pornography websites. To address the security problems and safety problems, the proposed system concentrates on the safety issues and security issues.