Analysis of Text Mining Techniques over Public Pages of Facebook

摘要

Spam is an unsolicited message, usually sent in the bulk. It is an unwanted activity that is performed to deceive people, to theft their personal information, to inject virus in their system, to redirect them on malicious sites. On OSN, spammers share malicious link looking like genuine one, place discount messages on their wall, develop malicious apps and sometimes create fake accounts. While on blog sites, Intruders use the portal for spreading rumors, mislead about certain campaign, and overload the forums with off-topic comments. When readers are only interested in reading strictly on-topic information, unrelated comments creates confusion. So It is necessary to analyze the unrelated content on online social media. In this paper, we have applied two text mining approaches to measure relatedness between posts and comments over two public pages India-forum.com and Wikipedia on Facebook.