Hate and Aggression Detection in Social Media Over Hindi English Language

K. Pareek, Arjun Choudhary, A. Tripathi, K. Mishra, Namita Mittal
{"title":"Hate and Aggression Detection in Social Media Over Hindi English Language","authors":"K. Pareek, Arjun Choudhary, A. Tripathi, K. Mishra, Namita Mittal","doi":"10.4018/ijssci.300357","DOIUrl":null,"url":null,"abstract":"In today’s time, everyone is familiar with social media platforms. It is quite helpful in connecting people. It has many advantages and some disadvantages too. Currently, in social media, hate and aggression have become a huge problem. On these platforms, many people make inflammatory posts targeting any person or society by using code mixed language, due to which many problems arise in the society. At the current time, much research work is being done on English language-related social media posts. The authors have focused on code mixed language. Authors have also tried to focus on sentences that do not use abusive words but contain hatred-related remarks. In this research, authors have used Natural Language Processing (NLP). Authors have applied Fasttext word embedding to the dataset. Fasttext is a technique of NLP. Deep learning (DL) classification algorithms were applied thereafter. In this research, two classifications have been used i.e. Convolutional Neural Network (CNN) and Bidirectional LSTM (Bi-LSTM).","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Softw. Sci. Comput. Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijssci.300357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In today’s time, everyone is familiar with social media platforms. It is quite helpful in connecting people. It has many advantages and some disadvantages too. Currently, in social media, hate and aggression have become a huge problem. On these platforms, many people make inflammatory posts targeting any person or society by using code mixed language, due to which many problems arise in the society. At the current time, much research work is being done on English language-related social media posts. The authors have focused on code mixed language. Authors have also tried to focus on sentences that do not use abusive words but contain hatred-related remarks. In this research, authors have used Natural Language Processing (NLP). Authors have applied Fasttext word embedding to the dataset. Fasttext is a technique of NLP. Deep learning (DL) classification algorithms were applied thereafter. In this research, two classifications have been used i.e. Convolutional Neural Network (CNN) and Bidirectional LSTM (Bi-LSTM).
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
印地语英语社交媒体中的仇恨和攻击检测
在当今时代,每个人都熟悉社交媒体平台。它在联系人们方面很有帮助。它有很多优点和缺点。目前,在社交媒体上,仇恨和攻击已经成为一个巨大的问题。在这些平台上,许多人使用代码混合语言发布针对任何人或社会的煽动性帖子,因此在社会上产生了许多问题。目前,人们正在对与英语相关的社交媒体帖子进行大量研究。作者专注于代码混合语言。作者们也试图把重点放在不使用辱骂性词语,但包含仇恨相关言论的句子上。在这项研究中,作者使用了自然语言处理(NLP)。作者将Fasttext词嵌入应用于数据集。快速文本是一种NLP技巧。随后应用深度学习(DL)分类算法。在本研究中,使用了卷积神经网络(CNN)和双向LSTM (Bi-LSTM)两种分类方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Knowledge Discovery of Hospital Medical Technology Based on Partial Ordered Structure Diagrams Artificial Intelligence Techniques to improve cognitive traits of Down Syndrome Individuals: An Analysis TA-WHI: Text Analysis of Web-Based Health Information Detection of Distributed Denial of Service (DDoS) Attacks Using Computational Intelligence and Majority Vote-Based Ensemble Approach Model-Based Method for Optimisation of an Adaptive System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1