On Social Networks, Spammer Detection and Fake User Identification (A: Review)

Abstract

Social networking services are used by millions of individuals all around the world. Users' interactions with these social media networks, Take, for example, Twitter and Facebook. , and have a significant impact on daily life, with occasionally negative outcomes. Spammers have turned prominent social media sites into a target for transmitting a vast amount of irrelevant and dangerous information. . Twitter, For instance, has become one of the most popular platforms of all time. , allowing an overwhelming volume of spam to enter the system Fake users send unwelcome tweets to users in order to promote businesses or websites, which not only disrupts resource consumption but also affects actual users.  . Furthermore, the potential to disseminate incorrect information to people using fraudulent identities has increased. . Furthermore, the potential to disseminate incorrect information to people using fraudulent identities has increased. , as a result of which hazardous stuff is spread. In today's online social networks, detecting spammers and identifying fraudulent users on Twitter has lately become a popular research issue (OSNs). In this paper, we'll look at, we’ll take a look after that, we'll look at some of the methods for detecting spammers on Twitter. . A taxonomy of Twitter spam detection systems is also provided, which categorizes the tactics into four groups according on their ability to recognize I false information. , (ii) spam based on URL, (iii) spam in hot topics, and (iv) fake users. The approaches offered are also contrasted based on a variety of factors, including user attributes. , qualities of the content, graph characteristics, and structural characteristics , as well as temporal features We feel that the information presented here will be a valuable resource for academics looking for the most recent advances in Twitter spam detection in one location.