Research And Experiment Of A Social Spammer Detection Algorithm

In recent years,with the rapid development of 5G mobile communication,short video and other technologies,people share more of their lives on the Internet and interact more frequently on the Internet.Social network plays an increasingly important role in modern society,so there is an urgent need for a fully secure,reliable and real online social networking platform.But at the same time,a large number of spam senders have also poured into the social network platform,which has caused great trouble to the online social life of normal users of the platform,such as wasting users' time in small scale and causing users' economic losses in large scale.At the same time,the unlimited collection and use of users' personal information on social network platform further causes the risk of users' personal information being collected,leaked and spread by lawbreakers,which greatly damages the legitimate rights and interests of normal platform users.Therefore,spam sender detection for social network service platform is of great significance.However,the current excellent detection algorithm needs a lot of user information,which conflicts with personal information protection.With the importance of personal privacy data protection in China and the enhancement of people's awareness of personal privacy data protection,how to effectively detect the sender of social network spam information without using a lot of personal user information has become an important problem to be solved.Aiming at the problem of social spam sender detection,this paper proposes a detection method based on directed social network graph.This kind of method abstracts the social network as a social network graph,based on the performance difference between the spam sender and normal users in the social network,gives different false influence to each network node representing the user,and combines the user's account information to determine the spam sender.This paper reviews the current situation of social network spam sender detection technology,focuses on the use of various methods and technologies in user data,focuses on a spam sender detection technology that does not rely too much on user information,and proposes an improved algorithm.After the experiment and analysis based on real Weibo data sets,the correctness and effectiveness of the algorithm are verified.The experimental results show that the detection algorithm proposed in this paper can still complete the task of social spam sender detection in the case of limited user information use.