Social networks are fascinating and valuable datasets, which can be leveraged to better understand society, and to make inter-personal choices. This tutorial explores the fundamental issues that arise when storing and querying social data. The discussion is divided into three main parts. First, we consider some of the key computational problems that arise over the social graph structure, such as node centrality, link prediction, community detection and information diffusion. Second, we consider algorithmic challenges that leverage both the textual content and the graph structure of a social network, e.g., social search and querying, and team formation. Finally, we consider critical aspects of implementing a social network database management system, and discuss existing systems. In this tutorial, we also point out gaps between the state-of-the-art and desired features of a data management system for social networking, and discuss open research challenges.
|Title of host publication
|PODS 2016 - Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems
|Association for Computing Machinery
|Number of pages
|Published - 15 Jun 2016
|35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, PODS 2016 - San Francisco, United States
Duration: 26 Jun 2016 → 1 Jul 2016
|Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems
|35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, PODS 2016
|26/06/16 → 1/07/16
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