摘要：The registered user’s social activities have been tremendously increasing because of Twitter social network. The Online Social Network (OSN) in Twitter has dual performances, one function as micro blogging OSN and other is news update platform. Cybercriminals are more enticed due to rapid growth in Twitter social interactions in recent times. The distinct spam account identification plays a crucial step in the process of spammer’s network detection involving in these activities. Several policies and technologies have been developed by the researchers for potential spam activities prevention. Twitter spam detection and social network activities has been accomplished by numerous methodologies. The user’s information might be leaked by web pages and various activities though it possesses high security settings. Sharing of lot more information by means of social networks can lead hackers impersonating users as well as user friends into sharing personal data, affording restricted sites access, or downloading malware. Many researchers and scientists has been grabbed attention by this social network spam and presented numerous theories for spam categorization and recognition. This paper analyzes those twitter spam detection methods and provides a comparison between those methods and identifies the merits and demerits in the existing methodologies.
