{"title":"Twtrends -一个从twitter趋势中提取主题地图的可视化系统","authors":"J. Iio","doi":"10.33965/ijwi_2019172108","DOIUrl":null,"url":null,"abstract":"Twitter provides a list of trending topics, a list of social trends or issues that users of the social networking services (SNS) will be interested in at a given time. However, they are presented as a list of key phrases making it challenging to identify or infer the message of the trending topics. In an attempt decipher the meaning and the structure hidden in the list of trending topics provided by Twitter, we developed a system to visualize topic maps according to the co-occurrence structure of typical tweets that mention the trending topics. This paper describes an overview of the system structure, the main logic to construct topic maps, and a discussion on several findings from its operation between January 1 and June 30, 2019. Also the possibilities of modification to suit the system for the other languages is discussed.","PeriodicalId":245560,"journal":{"name":"IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"TWTRENDS — A VISUALIZATION SYSTEM ON TOPIC MAPS EXTRACTED FROM TWITTER TRENDS\",\"authors\":\"J. Iio\",\"doi\":\"10.33965/ijwi_2019172108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Twitter provides a list of trending topics, a list of social trends or issues that users of the social networking services (SNS) will be interested in at a given time. However, they are presented as a list of key phrases making it challenging to identify or infer the message of the trending topics. In an attempt decipher the meaning and the structure hidden in the list of trending topics provided by Twitter, we developed a system to visualize topic maps according to the co-occurrence structure of typical tweets that mention the trending topics. This paper describes an overview of the system structure, the main logic to construct topic maps, and a discussion on several findings from its operation between January 1 and June 30, 2019. Also the possibilities of modification to suit the system for the other languages is discussed.\",\"PeriodicalId\":245560,\"journal\":{\"name\":\"IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33965/ijwi_2019172108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33965/ijwi_2019172108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TWTRENDS — A VISUALIZATION SYSTEM ON TOPIC MAPS EXTRACTED FROM TWITTER TRENDS
Twitter provides a list of trending topics, a list of social trends or issues that users of the social networking services (SNS) will be interested in at a given time. However, they are presented as a list of key phrases making it challenging to identify or infer the message of the trending topics. In an attempt decipher the meaning and the structure hidden in the list of trending topics provided by Twitter, we developed a system to visualize topic maps according to the co-occurrence structure of typical tweets that mention the trending topics. This paper describes an overview of the system structure, the main logic to construct topic maps, and a discussion on several findings from its operation between January 1 and June 30, 2019. Also the possibilities of modification to suit the system for the other languages is discussed.
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