Open AccessIdentifying and Detecting Offensive Language in Social Media
Author(s) -
Sri Latha Boddu,
Srinivasa Bapiraju Gadiraju
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i7524.078919
Subject(s) - offensive , dialog box , population , computer science , social media , internet privacy , advertising , sentence , personality psychology , computer security , naive bayes classifier , psychology , social psychology , artificial intelligence , support vector machine , world wide web , personality , sociology , engineering , operations research , business , demography
The utilization of the social media destinations is developing quickly to interface with the networks and to share the thoughts among others. It might happen that a large portion of the general population disdain the thoughts of others individual perspectives and utilize their posts. Because of these hostile terms, numerous individuals particularly youth and young people endeavor to embrace which may fundamentally influence the others individual are honest personalities. As hostile terms progressively use by the general population in profoundly way, it is hard to discover or characterize such hostile terms in genuine day-to-day life. To defeat from this issue, the proposed system dissects the offensive words and can group the hostile sentence on a specific topic dialog utilizing the SVM as managed arrangement in the information mining. The proposed system additionally can locate the potential client by methods for which the hostile language spread among others and characterize the proportional analysis of SVM with Naive Bayes procedure. The proposed structure goes about as a screening instrument that cautions the customer about such messages