{"title":"基于网络指标的科学合作自动分类","authors":"Tilman Göhnert, A. Harrer, H. Hoppe","doi":"10.1109/ENIC.2014.20","DOIUrl":null,"url":null,"abstract":"In this paper we introduce a method and implementation to detect and classify specific episodes of scientific collaboration. Our method uses co-authorship networks and creates indicators for the discovery of temporal patterns of co-authoring. We apply the concept and implementation to scientific communities of the fields collaborative systems and social network analysis, to compare our findings to an earlier non-automated and small-scale analysis.","PeriodicalId":185148,"journal":{"name":"2014 European Network Intelligence Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Classification of Scientific Collaborations with Network Indicators\",\"authors\":\"Tilman Göhnert, A. Harrer, H. Hoppe\",\"doi\":\"10.1109/ENIC.2014.20\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we introduce a method and implementation to detect and classify specific episodes of scientific collaboration. Our method uses co-authorship networks and creates indicators for the discovery of temporal patterns of co-authoring. We apply the concept and implementation to scientific communities of the fields collaborative systems and social network analysis, to compare our findings to an earlier non-automated and small-scale analysis.\",\"PeriodicalId\":185148,\"journal\":{\"name\":\"2014 European Network Intelligence Conference\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 European Network Intelligence Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ENIC.2014.20\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 European Network Intelligence Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENIC.2014.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated Classification of Scientific Collaborations with Network Indicators
In this paper we introduce a method and implementation to detect and classify specific episodes of scientific collaboration. Our method uses co-authorship networks and creates indicators for the discovery of temporal patterns of co-authoring. We apply the concept and implementation to scientific communities of the fields collaborative systems and social network analysis, to compare our findings to an earlier non-automated and small-scale analysis.