{"title":"Twitter中的实时事件检测:一个案例研究","authors":"A. Sani, A. Moeini","doi":"10.1109/ICWR49608.2020.9122281","DOIUrl":null,"url":null,"abstract":"In this paper we present the study which uses hashing as a vectorizer and locality sensitive hashing to approximately find similar items, combined with incremental clustering to implement a practical real-time event detection algorithm. By gathering a substantial amount of Persian tweets, the proposed algorithm is evaluated. It is shown that the presented pipeline and methods are capable of detecting the events related to 7 out of 10 football matches during the days in which the Iranian national football team took part in the 2018 FIFA World Cup. A total of 102 events were detected with a precision of 87.25%.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Real-time Event Detection in Twitter: A Case Study\",\"authors\":\"A. Sani, A. Moeini\",\"doi\":\"10.1109/ICWR49608.2020.9122281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present the study which uses hashing as a vectorizer and locality sensitive hashing to approximately find similar items, combined with incremental clustering to implement a practical real-time event detection algorithm. By gathering a substantial amount of Persian tweets, the proposed algorithm is evaluated. It is shown that the presented pipeline and methods are capable of detecting the events related to 7 out of 10 football matches during the days in which the Iranian national football team took part in the 2018 FIFA World Cup. A total of 102 events were detected with a precision of 87.25%.\",\"PeriodicalId\":231982,\"journal\":{\"name\":\"2020 6th International Conference on Web Research (ICWR)\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 6th International Conference on Web Research (ICWR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWR49608.2020.9122281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Web Research (ICWR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWR49608.2020.9122281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time Event Detection in Twitter: A Case Study
In this paper we present the study which uses hashing as a vectorizer and locality sensitive hashing to approximately find similar items, combined with incremental clustering to implement a practical real-time event detection algorithm. By gathering a substantial amount of Persian tweets, the proposed algorithm is evaluated. It is shown that the presented pipeline and methods are capable of detecting the events related to 7 out of 10 football matches during the days in which the Iranian national football team took part in the 2018 FIFA World Cup. A total of 102 events were detected with a precision of 87.25%.
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