{"title":"Visualizing e-government emerging and fading themes using SNA techniques","authors":"Seyed Mohammad JafarJalali","doi":"10.1109/ECDC.2016.7492983","DOIUrl":null,"url":null,"abstract":"Social network analysis (SNA) method is characterized as a structured technique for providing so as to analyse the connections within the networks by visualizing and analyzing relationships among documents, individuals, and even whole associations. The fundamental point of this research was to analyze the 4720 scientific documents on the field of E-Government through SNA techniques which decomposed the networks of the keywords of E-Government domain incorporated into the Web of Science Core Collection, a well-known scientific dataset during a time span of 20 years from 1995 to 2015. The algorithm of Burst Detection has been utilized for investigating the emergent trends and visualization of the E-Government domain. This study highlights the the most active research fronts of e-government, providing a research-based platform for further scholarly discussions.","PeriodicalId":253363,"journal":{"name":"2016 10th International Conference on e-Commerce in Developing Countries: with focus on e-Tourism (ECDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Conference on e-Commerce in Developing Countries: with focus on e-Tourism (ECDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECDC.2016.7492983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Social network analysis (SNA) method is characterized as a structured technique for providing so as to analyse the connections within the networks by visualizing and analyzing relationships among documents, individuals, and even whole associations. The fundamental point of this research was to analyze the 4720 scientific documents on the field of E-Government through SNA techniques which decomposed the networks of the keywords of E-Government domain incorporated into the Web of Science Core Collection, a well-known scientific dataset during a time span of 20 years from 1995 to 2015. The algorithm of Burst Detection has been utilized for investigating the emergent trends and visualization of the E-Government domain. This study highlights the the most active research fronts of e-government, providing a research-based platform for further scholarly discussions.