• M. Mallikarjunarao
• D Anveshini
• Kakumanu. Pavani Venkata Amrutha
• Kambala. Krishnaveni
• Bhavanari. Rishitha, Shaik. Anusha, Ravi. Sri Tulasi

Almost everyone in the world makes use of social networking services. The daily life of many people including me is highly influenced by how the users interact with them on social platforms such as Twitter and Instagram. At present, social network sites are part of life for most people. Platforms for social media like Twitter, Instagram, and others have a big impact on our lives. Across the world, people are actively engaged in it. Popular social networking sites have been used as a target by spammers to spread a lot of harmful and irrelevant data. In Now a day’s online social networks, finding spammers and fraudulent users on Twitter has recently become a hot research area (OSNs).phoney content, based on URL spam, The availability of the vast amount of information and their open nature attracts the interest of cybercriminals to create steal data. Malicious bots in these platforms are automated or semi-automated entities used in nefarious ways while simulating human behaviour. The architecture and hyper parameters are also discussed in this session.

OSN, Spam, fake account, URL, twitter, social media

"FAKE PROFILE IDENTIFICATION IN SOCIAL NETWORK USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.54-64, November-2024, Available :http://www.jetir.org/papers/JETIRGO06006.pdf

"FAKE PROFILE IDENTIFICATION IN SOCIAL NETWORK USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp54-64, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06006.pdf