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INTERNATIONAL JOURNAL OF INNOVATIONS IN APPLIED SCIENCES & ENGINEERINGInternational Peer Reviewed (Refereed), Open Access Research Journal (By Aryavart International University, India) E-ISSN:2454-9258 | P-ISSN:2454-809X | Estd Year: 2015 Impact Factor(2021): 5.246 | Impact Factor(2022): 5.605 |
Aditya Goel
Vol. 5, Jan-Dec 2019
Page Number: 152 - 158
Abstract:
As the web develops rapidly, social networking interpersonal communications have become an essential part of day to day life where individuals can chat with one another, spreading interactive media data. Subsequently, online informal communication locales are ideal for general trading sentiments. Online social networking interpersonal communication locales give safety efforts, yet they are restricted. In OSN websites like Facebook, Twitter, and others, there is a chance of posting any sort of information on client walls. Where such kind of messages and pictures which would be unsafe and leads to distraction using OSN websites. To prevent this problem, we propose a system that provides a facility through which the client can control posting an unwanted message on their Facebook walls by using a short content classifier and AI text analysis. Furthermore, undesirable pictures are confined by utilizing KNN classification.