{"title":"Examining Different Research Communities: Authorship Network","authors":"Shrabani Ghosh","doi":"arxiv-2409.00081","DOIUrl":null,"url":null,"abstract":"Google Scholar is one of the top search engines to access research articles\nacross multiple disciplines for scholarly literature. Google scholar advance\nsearch option gives the privilege to extract articles based on phrases,\npublishers name, authors name, time duration etc. In this work, we collected\nGoogle Scholar data (2000-2021) for two different research domains in computer\nscience: Data Mining and Software Engineering. The scholar database resources\nare powerful for network analysis, data mining, and identify links between\nauthors via authorship network. We examined coauthor-ship network for each\ndomain and studied their network structure. Extensive experiments are performed\nto analyze publications trend and identifying influential authors and\naffiliated organizations for each domain. The network analysis shows that the\nnetworks features are distinct from one another and exhibit small communities\nwithin the influential authors of a particular domain.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"59 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Digital Libraries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.00081","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
Google Scholar is one of the top search engines to access research articles
across multiple disciplines for scholarly literature. Google scholar advance
search option gives the privilege to extract articles based on phrases,
publishers name, authors name, time duration etc. In this work, we collected
Google Scholar data (2000-2021) for two different research domains in computer
science: Data Mining and Software Engineering. The scholar database resources
are powerful for network analysis, data mining, and identify links between
authors via authorship network. We examined coauthor-ship network for each
domain and studied their network structure. Extensive experiments are performed
to analyze publications trend and identifying influential authors and
affiliated organizations for each domain. The network analysis shows that the
networks features are distinct from one another and exhibit small communities
within the influential authors of a particular domain.
Google Scholar 是访问跨学科学术文献研究文章的顶级搜索引擎之一。谷歌学者的高级搜索选项提供了根据短语、出版商名称、作者姓名、时间长度等提取文章的特权。在这项工作中,我们收集了计算机科学领域两个不同研究领域的谷歌学术数据(2000-2021 年):数据挖掘和软件工程。学者数据库资源具有强大的网络分析和数据挖掘功能,可通过作者关系网络识别作者之间的联系。我们检查了每个领域的合著者关系网络,并研究了它们的网络结构。我们进行了广泛的实验,以分析每个领域的论文发表趋势,并识别有影响力的作者和附属机构。网络分析结果表明,这些网络特征彼此不同,并在特定领域有影响力的作者中呈现出小社区的特征。