{"title":"使用暹罗网络和快速文本表示的受损Tweet检测","authors":"Mihir Joshi, Parmeet Singh, A. N. Zincir-Heywood","doi":"10.23919/CNSM46954.2019.9012722","DOIUrl":null,"url":null,"abstract":"The aim of this work is to detect compromised users of tweets based on their writing styles. In this paper, we use Siamese Networks to learn a representation of user tweets that allows us to classify them based on a limited amount of ground truth data. We propose the employment of this classification model to identify compromised user accounts of tweets.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Compromised Tweet Detection Using Siamese Networks and fastText Representations\",\"authors\":\"Mihir Joshi, Parmeet Singh, A. N. Zincir-Heywood\",\"doi\":\"10.23919/CNSM46954.2019.9012722\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this work is to detect compromised users of tweets based on their writing styles. In this paper, we use Siamese Networks to learn a representation of user tweets that allows us to classify them based on a limited amount of ground truth data. We propose the employment of this classification model to identify compromised user accounts of tweets.\",\"PeriodicalId\":273818,\"journal\":{\"name\":\"2019 15th International Conference on Network and Service Management (CNSM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 15th International Conference on Network and Service Management (CNSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CNSM46954.2019.9012722\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 15th International Conference on Network and Service Management (CNSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CNSM46954.2019.9012722","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compromised Tweet Detection Using Siamese Networks and fastText Representations
The aim of this work is to detect compromised users of tweets based on their writing styles. In this paper, we use Siamese Networks to learn a representation of user tweets that allows us to classify them based on a limited amount of ground truth data. We propose the employment of this classification model to identify compromised user accounts of tweets.
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