Data management for social networking

Sara Cohen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

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.

Original languageAmerican English
Title of host publicationPODS 2016 - Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems
PublisherAssociation for Computing Machinery
Pages165-177
Number of pages13
ISBN (Electronic)9781450341912
DOIs
StatePublished - 15 Jun 2016
Event35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, PODS 2016 - San Francisco, United States
Duration: 26 Jun 20161 Jul 2016

Publication series

NameProceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems
Volume26-June-01-July-2016

Conference

Conference35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, PODS 2016
Country/TerritoryUnited States
CitySan Francisco
Period26/06/161/07/16

Bibliographical note

Publisher Copyright:
© 2016 ACM.

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