基于文本分类的假新闻识别研究

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI:10.1109/SPAC46244.2018.8965536

Shenhao Zhang, Yihui Wang, Chengxiang Tan

{"title":"基于文本分类的假新闻识别研究","authors":"Shenhao Zhang, Yihui Wang, Chengxiang Tan","doi":"10.1109/SPAC46244.2018.8965536","DOIUrl":null,"url":null,"abstract":"In the big data environment, massive news can always lead people to make their own judgments about events happening in society. The wrong guidance of fake news will lead to a negative effect on society. It is necessary to distinguish between real and fake news. In the traditional text categorization method, using the TF-IDF information of the words in the document as the weight matrix and applying it to the classifier. Inevitably, TF-IDF contains limited information, limiting the effect of classification. This paper proposed a method based on TF-IDF and Word2vec for identifying fake news, using SVM to verify its validity.","PeriodicalId":360369,"journal":{"name":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Research on Text Classification for Identifying Fake News\",\"authors\":\"Shenhao Zhang, Yihui Wang, Chengxiang Tan\",\"doi\":\"10.1109/SPAC46244.2018.8965536\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the big data environment, massive news can always lead people to make their own judgments about events happening in society. The wrong guidance of fake news will lead to a negative effect on society. It is necessary to distinguish between real and fake news. In the traditional text categorization method, using the TF-IDF information of the words in the document as the weight matrix and applying it to the classifier. Inevitably, TF-IDF contains limited information, limiting the effect of classification. This paper proposed a method based on TF-IDF and Word2vec for identifying fake news, using SVM to verify its validity.\",\"PeriodicalId\":360369,\"journal\":{\"name\":\"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAC46244.2018.8965536\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC46244.2018.8965536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 11

摘要

在大数据环境下，海量的新闻总是会让人们对社会上正在发生的事件做出自己的判断。假新闻的错误引导会对社会产生负面影响。区分真假新闻是必要的。在传统的文本分类方法中，使用文档中单词的TF-IDF信息作为权重矩阵应用到分类器中。TF-IDF不可避免地包含有限的信息，限制了分类的效果。本文提出了一种基于TF-IDF和Word2vec的假新闻识别方法，并使用SVM对其有效性进行验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Research on Text Classification for Identifying Fake News

In the big data environment, massive news can always lead people to make their own judgments about events happening in society. The wrong guidance of fake news will lead to a negative effect on society. It is necessary to distinguish between real and fake news. In the traditional text categorization method, using the TF-IDF information of the words in the document as the weight matrix and applying it to the classifier. Inevitably, TF-IDF contains limited information, limiting the effect of classification. This paper proposed a method based on TF-IDF and Word2vec for identifying fake news, using SVM to verify its validity.

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

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)

自引率

0.00%

发文量