Visualization of SPAM Patterns in Social Network

Twitter within the existing social network with friends and to maintain the benefits in the various businesses, individuals spam by spammers. Following tweet exposed to a large number of users, has had trouble. In previous research studies conducted on these spam tweets cases, but the lack of sophistication due to many causes and more precise classification and the results were difficult to detect. Main features of the spammers, classification, classification methods are described. These characteristics of the link rate and followers/ following one class and one class through the spammers account the difference between the proposed criteria for classification. This experiment was performed according to the criteria. Randomized trial of spam and non-spam accounts were selected account type was conducted according to the criteria 68% of the link rate of spam accounts, followers / following ratio was 27581.5. 6.12% non-spam accounts, followers / following ratio was 1.26. In the end we were to visualize the results.