{"title":"Graph Summarization for Geo-correlated Trends Detection in Social Networks","authors":"Colin Biafore, Faisal Nawab","doi":"10.1145/2882903.2914832","DOIUrl":null,"url":null,"abstract":"Trends detection in social networks is possible via a multitude of models with different characteristics. These models are pre-defined and rigid which creates the need to expose the social network graph to data scientists to introduce the human-element in trends detection. However, inspecting large social network graphs visually is tiresome. We tackle this problem by providing effective graph summarizations aimed at the application of geo-correlated trends detection in social networks.","PeriodicalId":20483,"journal":{"name":"Proceedings of the 2016 International Conference on Management of Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2882903.2914832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Trends detection in social networks is possible via a multitude of models with different characteristics. These models are pre-defined and rigid which creates the need to expose the social network graph to data scientists to introduce the human-element in trends detection. However, inspecting large social network graphs visually is tiresome. We tackle this problem by providing effective graph summarizations aimed at the application of geo-correlated trends detection in social networks.
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