{"title":"基于twitter的数据挖掘软件系统","authors":"F. Bhat, M. Oussalah, K. Challis, T. Schnier","doi":"10.1109/CIS.2011.6169149","DOIUrl":null,"url":null,"abstract":"The rise of social network usage through mobile devices makes the rigorous analysis of these systems of paramount importance for intelligence gathering and decision making. This paper describes the outcome of a multidisciplinary project carried out for the purpose of Twitter data collection and analysis. In particular, a proposal for enabling the discovery of spatial patterns within geo-located Twitter content has been investigated and implemented.","PeriodicalId":286889,"journal":{"name":"2011 IEEE 10th International Conference on Cybernetic Intelligent Systems (CIS)","volume":"461 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A software system for data mining with twitter\",\"authors\":\"F. Bhat, M. Oussalah, K. Challis, T. Schnier\",\"doi\":\"10.1109/CIS.2011.6169149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rise of social network usage through mobile devices makes the rigorous analysis of these systems of paramount importance for intelligence gathering and decision making. This paper describes the outcome of a multidisciplinary project carried out for the purpose of Twitter data collection and analysis. In particular, a proposal for enabling the discovery of spatial patterns within geo-located Twitter content has been investigated and implemented.\",\"PeriodicalId\":286889,\"journal\":{\"name\":\"2011 IEEE 10th International Conference on Cybernetic Intelligent Systems (CIS)\",\"volume\":\"461 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 10th International Conference on Cybernetic Intelligent Systems (CIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2011.6169149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 10th International Conference on Cybernetic Intelligent Systems (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2011.6169149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The rise of social network usage through mobile devices makes the rigorous analysis of these systems of paramount importance for intelligence gathering and decision making. This paper describes the outcome of a multidisciplinary project carried out for the purpose of Twitter data collection and analysis. In particular, a proposal for enabling the discovery of spatial patterns within geo-located Twitter content has been investigated and implemented.