Article,
A Survey of Methods for Spotting Spammers on Twitter
INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 7 (3): 694-702 (June 2023)
Abstract
Social networking sites explosive expansion as a means of information sharing, management, communication, storage, and management has attracted hackers who abuse the Web to take advantage of security flaws for their own nefarious ends. Every day, forged internet accounts are compromised. Online social networks OSNs are rife with impersonators, phishers, scammers, and spammers who are difficult to spot. Users who send unsolicited communications to a large audience with the objective of advertising a product, entice victims to click on harmful links, or infect users systems only for financial gain are known as spammers. Many studies have been conducted to identify spam profiles in OSNs. In this essay, we have discussed the methods currently in use to identify spam Twitter users. User based, content based, or a combination of both features could be used to identify spammers. The current paper gives a summary of the traits, methodologies, detection rates, and restrictions if any for identifying spam profiles, primarily on Twitter. Hareesha Devi | Pankaj Verma | Ankit Dhiman Ä Survey of Methods for Spotting Spammers on Twitter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd57439.pdf Paper URL: https://www.ijtsrd.com.com/computer-science/artificial-intelligence/57439/a-survey-of-methods-for-spotting-spammers-on-twitter/hareesha-devi
