Open AccessANALYSIS OF VARIOUS APPROACHES OF ABUSIVE TEXT DETECTION IN ONLINE SOCIAL NETWORKS
Publication year - 2021
Publication title -
international journal for innovative engineering and management research
Language(s) - English
Resource type - Journals
ISSN - 2456-5083
DOI - 10.48047/ijiemr/v10/i11/18
Subject(s) - offensive , computer science , hindi , bengali , social media , telugu , urdu , artificial intelligence , identification (biology) , language identification , natural language processing , task (project management) , world wide web , linguistics , natural language , mathematics , philosophy , botany , operations research , biology , management , economics
Social media is one of the most influential tool for sharing information across different regions among differentusers .The people sharing their interests in various aspects in online social networking platforms like Facebook,twitter etc. Therefore the usage of hate text steadily increasing. Nowadays it has been reviled unfair behavior of theusers in social networking sites. The existence of abusive text on different online social networking platforms andidentification of such text is a big challenging task. To understand the complexity of language constructs indifferent languages is very difficult .Already lot of research work has completed in English language. This papergives detail analysis of detecting hate text in various languages Hindi, urdu, Arabic, Bengali, Telugu. Weincorporated various kinds of ML and DL based algorithms to identify hate text in OSN’s. A review is done relatedto different classifiers where a comparison made between different models of ML, DL algorithms. Finally finds theaccurate method to classify the text is offensive or not by finding the parameters i.e. accuracy and F1score