Open AccessThe Spammer Detection and Fake User Identification on Social Networks
Author(s) -
C. Gomathy
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.38760
Subject(s) - spamming , identification (biology) , internet privacy , computer science , fake news , world wide web , social network (sociolinguistics) , social media , computer security , the internet , botany , biology
The Twitter has fleetly come an online source for acquiring real- time his/ her information about druggies. Twitter is an Online Social Network (OSN) where druggies can partake anything and everything, similar as news, opinions, and indeed their moods. Several arguments can be held over different motifs, similar as politics, Perticular affairs, and important events. When a stoner tweets commodity, it's incontinently conveyed to her followers, allowing them to unfold the entered information at a much broader position. With the elaboration of OSNs, the need to study and dissect druggies' actions in online social platforms has intensity Spammers can be linked grounded on (i) fake content, (ii) URL grounded spam discovery, (iii) spam in trending motifs, and (iv) fake stoner identification. And with the help of machine literacy algorithms we're going to identify the fake stoner and spammer in twitter. Keywords: Online Social Network, Spammers Identification, Fake User Identification.