社会网络-词嵌入方法在仇恨言论检测中的研究

Bayu Nugroho
{"title":"社会网络-词嵌入方法在仇恨言论检测中的研究","authors":"Bayu Nugroho","doi":"10.29080/systemic.v7i2.1771","DOIUrl":null,"url":null,"abstract":"Word embedding is a technique to represent sentences in vector space. The representation itself is carried-out to build a model that would suffice in representing a particular task related to the use of the sentence itself, for example, a model of similarity among sentences/words, a model of Twitter user connectivity, and demographics of tweets model. The use of word embedding is a handful to the sentiment analysis research because it helps build a mathematical-friendly model from sentences. The model then will be suitable as feeds for the other computational process.","PeriodicalId":126624,"journal":{"name":"Systemic: Information System and Informatics Journal","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Survey of Social Network - Word Embedding Approach for Hate Speeches Detection\",\"authors\":\"Bayu Nugroho\",\"doi\":\"10.29080/systemic.v7i2.1771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Word embedding is a technique to represent sentences in vector space. The representation itself is carried-out to build a model that would suffice in representing a particular task related to the use of the sentence itself, for example, a model of similarity among sentences/words, a model of Twitter user connectivity, and demographics of tweets model. The use of word embedding is a handful to the sentiment analysis research because it helps build a mathematical-friendly model from sentences. The model then will be suitable as feeds for the other computational process.\",\"PeriodicalId\":126624,\"journal\":{\"name\":\"Systemic: Information System and Informatics Journal\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Systemic: Information System and Informatics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29080/systemic.v7i2.1771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systemic: Information System and Informatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29080/systemic.v7i2.1771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

词嵌入是一种在向量空间中表示句子的技术。执行表示本身是为了构建一个足以表示与句子本身使用相关的特定任务的模型,例如句子/单词之间的相似性模型、Twitter用户连通性模型和tweet的人口统计模型。词嵌入的使用是情感分析研究的一个重要组成部分,因为它有助于从句子中建立一个数学友好的模型。然后,该模型将适合作为其他计算过程的馈源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Social Network - Word Embedding Approach for Hate Speeches Detection
Word embedding is a technique to represent sentences in vector space. The representation itself is carried-out to build a model that would suffice in representing a particular task related to the use of the sentence itself, for example, a model of similarity among sentences/words, a model of Twitter user connectivity, and demographics of tweets model. The use of word embedding is a handful to the sentiment analysis research because it helps build a mathematical-friendly model from sentences. The model then will be suitable as feeds for the other computational process.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信