Tanveer Ahmed, Adeel Ahmed, Mubashir Ali, M. Kamran
{"title":"用中心性方法分析计算机网络中的合著者","authors":"Tanveer Ahmed, Adeel Ahmed, Mubashir Ali, M. Kamran","doi":"10.1109/C-CODE.2017.7918901","DOIUrl":null,"url":null,"abstract":"Assorted communication on social networks attracted researcher's attention in recent time. Massive sharing of opinions, ideas, experiences and expertise highlight communication through social networks. Social networks have becoming a flourishing network for sharing such values. Identifying and analyzing these communication trends have gained importance for detecting patterns among peoples in social networks using community detection. Different methods have been proposed for detecting communities in social networks. Co-authorship network is also becoming central point of attention to many researchers. Domain specific co-authorship community detection is evolving area that is emerging beside other community detection identification patterns. In this paper, we performed analysis on coauthorship network in the field of computer networks using common centrality measures. Finding reveals that this study finds domain specific co-authors that are best in their knowledge sharing and collaboration in the field of computer networks.","PeriodicalId":344222,"journal":{"name":"2017 International Conference on Communication, Computing and Digital Systems (C-CODE)","volume":"207 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Analysis of co-authorship in computer networks using centrality measures\",\"authors\":\"Tanveer Ahmed, Adeel Ahmed, Mubashir Ali, M. Kamran\",\"doi\":\"10.1109/C-CODE.2017.7918901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Assorted communication on social networks attracted researcher's attention in recent time. Massive sharing of opinions, ideas, experiences and expertise highlight communication through social networks. Social networks have becoming a flourishing network for sharing such values. Identifying and analyzing these communication trends have gained importance for detecting patterns among peoples in social networks using community detection. Different methods have been proposed for detecting communities in social networks. Co-authorship network is also becoming central point of attention to many researchers. Domain specific co-authorship community detection is evolving area that is emerging beside other community detection identification patterns. In this paper, we performed analysis on coauthorship network in the field of computer networks using common centrality measures. Finding reveals that this study finds domain specific co-authors that are best in their knowledge sharing and collaboration in the field of computer networks.\",\"PeriodicalId\":344222,\"journal\":{\"name\":\"2017 International Conference on Communication, Computing and Digital Systems (C-CODE)\",\"volume\":\"207 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Communication, Computing and Digital Systems (C-CODE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/C-CODE.2017.7918901\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Communication, Computing and Digital Systems (C-CODE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/C-CODE.2017.7918901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of co-authorship in computer networks using centrality measures
Assorted communication on social networks attracted researcher's attention in recent time. Massive sharing of opinions, ideas, experiences and expertise highlight communication through social networks. Social networks have becoming a flourishing network for sharing such values. Identifying and analyzing these communication trends have gained importance for detecting patterns among peoples in social networks using community detection. Different methods have been proposed for detecting communities in social networks. Co-authorship network is also becoming central point of attention to many researchers. Domain specific co-authorship community detection is evolving area that is emerging beside other community detection identification patterns. In this paper, we performed analysis on coauthorship network in the field of computer networks using common centrality measures. Finding reveals that this study finds domain specific co-authors that are best in their knowledge sharing and collaboration in the field of computer networks.