Monitoring Suspicious News on Online Forum

Abstract

Suspicious news always createsrumors. In thistime, this problem isseen more on the Internet. Because, now-a-days people are almost stagnant without internet. And by exploiting this problem, evil organizations are doing many illegal activities and deceiving people. The ilaw ienforcement iagencies iare ilooking iforisolutionsito imonitor ithese idiscussion iforumsifor ipossible icriminal iactivitiesiand idownload isuspected ipostings ias ievidence ifor iinvestigation. iWe ipropose ia isystem iwhich iwill itackle ithis iproblem ieffectively. Our proposed system will download postings from selected discussion forums continuously and checking through our system techniques to identification. In this project we had used data mining, text mining, web mining, Naïve Bayes and Confusion Matrix to detect illegal postings. This system analysis online plain text sources such as Internet news, blogs, etc. This is done with the help of web mining and text mining concept. Also, using the NLP techniques and data mining concept for pre- processing the data. Finally, using the Confusion Matrix and Naïve Bayes algorithm to detect illegal postings. This system will help to reduce many illegal activities which are held on internet.