Paper Title
Spam-Slam
Article Identifiers
Authors
Yalini S , Jeevaprasath M , Preethi Anselin J , Tamilarasan S , Priyadharshini S
Keywords
Fake user detection,Spamming techniques,Taxonomy of spam detection approaches,User features
Abstract
Social networking sites engage millions of users around the world. The users’ interactions with these social sites, such as Twitter and Facebook have a tremendous impact and occasionally undesirable repercussions for daily life. The prominent social networking sites have turned into a target platform for the spammers to disperse a huge amount of irrelevant and deleterious information. Twitter, for example, has become one of the most extravagantly used platforms of all times and therefore allows an unreasonable amount of spam. Fake users send undesired tweets to users to promote services or websites that not only affect legitimate users but also disrupt resource consumption. Moreover, the possibility of expanding invalid information to users through fake identities has increased that results in the unrolling of harmful content. Recently, the detection of spammers and identification of fake users on Twitter has become a common area of research in contemporary online social Networks (OSNs). In this paper, we perform a review of techniques used for detecting spammers on Twitter. Moreover, a taxonomy of the Twitter spam detection approaches is presented that classifies the techniques based on their ability to detect: (i) fake content, (ii) spam based on URL, (iii) spam in trending topics, and (iv) fake users. The presented techniques are also compared based on various features, such as user features, content features, graph features, structure features, and time features. We are hopeful that the presented study will be a useful resource for researchers to find the highlights of recent developments in Twitter spam detection on a single platform.
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How To Cite (APA)
Yalini S, Jeevaprasath M, Preethi Anselin J, Tamilarasan S, & Priyadharshini S (May-2024). Spam-Slam. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), g46-g52. https://ijnrd.org/papers/IJNRD2405607.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : g46-g52
Other Publication Details
Paper Reg. ID: IJNRD_221033
Published Paper Id: IJNRD2405607
Downloads: 000121984
Research Area: Information TechnologyÂ
Country: Madurai, Tamilnadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405607.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405607
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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