Extracting Ego-Centric Social Networks from Linked Open Data

Raji Ghawi, Mirco Schönfeld, J. Pfeffer
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引用次数: 2

Abstract

Linked Open Data (LOD) refers to freely available data on the WWW that are typically represented using Resource Description Framework (RDF). LOD is an invaluable source of rich and structured information, and enables a wide range of new applications, such as Social Network Analysis (SNA). In this paper, we address the extraction of social networks from LOD using SPARQL language, and we present various patterns to extract ego-centric networks. We also present two case studies: i) influence networks of intellectuals, and ii) co-acting networks, to demonstrate the applicability and usefulness of the approach. CCS CONCEPTS • Information systems → Data extraction and integration; Social networks; Resource Description Framework (RDF).
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从关联的开放数据中提取以自我为中心的社交网络
链接开放数据(LOD)指的是WWW上免费提供的数据,这些数据通常使用资源描述框架(RDF)表示。LOD是丰富和结构化信息的宝贵来源,支持广泛的新应用程序,例如社会网络分析(Social Network Analysis, SNA)。在本文中,我们使用SPARQL语言解决了从LOD中提取社交网络的问题,并提出了各种模式来提取以自我为中心的网络。我们还提出了两个案例研究:i)知识分子的影响网络和ii)合作网络,以证明该方法的适用性和有用性。•信息系统→数据提取和集成;社交网络;资源描述框架(RDF)。
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