Hate Speech Detection on Social Media Using Machine Learning Algorithms

A. Admin, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa
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引用次数: 3

Abstract

There is an enormous growth of social media which fully promotes freedom of expression through its anonymity feature. Freedom of expression is a human right but hate speech towards a person or group based on race, caste, religion, ethnic or national origin, sex, disability, gender identity, etc. is an abuse of this sovereignty. It seriously promotes violence or hate crimes and creates an imbalance in society by damaging peace, credibility, and human rights, etc. To overcome this problem, the hate speech detection model is made which will classify the speech and if the speech used by user is containing hate word, it will be detected and system will sent an alert message to user about it. In order to solve various hate speech problems we use some of the machine learning algorithms such as logistic regression and random forest. If user disrupts cyber guidelines, then strict action shall be taken and user’s account will be ban forever. This help to reduce cyber crimes in effective and efficient manner.
使用机器学习算法检测社交媒体上的仇恨言论
社交媒体的迅猛发展,通过其匿名的特点充分促进了言论自由。言论自由是一项人权,但基于种族、种姓、宗教、族裔或民族、性别、残疾、性别认同等原因对个人或群体发表仇恨言论是对这一主权的滥用。它严重助长暴力或仇恨犯罪,并通过破坏和平、信誉和人权等造成社会不平衡。为了克服这一问题,提出了仇恨语音检测模型,该模型对用户使用的语音进行分类,如果用户使用的语音中含有仇恨词,系统将对其进行检测,并向用户发送警告信息。为了解决各种各样的仇恨言论问题,我们使用了一些机器学习算法,如逻辑回归和随机森林。如果用户破坏网络准则,将采取严厉措施,用户的账户将被永久封禁。这有助有效及有效率地减少网络罪案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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