MONITORING SUSPICIOUS DISCUSSIONS ON ONLINE FORUMS USING DATA MINING
People now-a-days are very fond of using internet as a discussion medium. As internet technology had been increasing more and more, this technology led to many legal and illegal activities.
It is found that much first-hand news has been discussed in Internet forums well before they are reported in traditional mass media. This communication channel provides an effective channel for illegal activities such as dissemination of copyrighted movies, threatening messages and online gambling etc.
The law enforcement agencies are looking for solutions to monitor these discussion forums for possible criminal activities and download suspected postings as evidence for investigation.
We propose a system which will tackle this problem effectively. In this project we had used a data mining algorithm to detect criminal activities and illegal postings. Our proposed system will download postings from selected discussion forums continuously and employ data mining techniques to identify hot topics and cluster authors into different groups using word-based user profiles.
This system will use text data mining technique. This system monitors and analysis online plain text sources such as Internet news, blogs, etc. for security purposes. This is done with the help of text mining concept. High-quality information is typically derived through the devising of patterns and trends. System will analyze online plain text sources from selected discussion forums and will classify the text into different groups and system will decide which post is legal and illegal. This system will help to reduce many illegal activities which are held on internet.