The longitudinal use of SaNDVis: Visual social network analytics in the enterprise

Adam Perer, Ido Guy, Erel Uziel, Inbal Ronen, Michal Jacovi

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

As people continue to author and share increasing amounts of information in social media, the opportunity to leverage such information for relationship discovery tasks increases. In this paper, we describe a set of systems that mine, aggregate, and infer a social graph from social media inside an enterprise, resulting in over 73 million relationships between 450,000 people. We then describe SaNDVis, a novel visual analytics tool that supports people-centric tasks like expertise location, team building, and team coordination in the enterprise. We provide details of a 22-month-long, large-scale deployment to over 2,300 users from which we analyze longitudinal usage patterns, classify types of visual analytics queries and users, and extract dominant use cases from log and interview data. By integrating social position, evidence, and facets into SaNDVis, we demonstrate how users can use a visual analytics tool to reflect on existing relationships as well as build new relationships in an enterprise setting.

Original languageEnglish
Article number6381408
Pages (from-to)1095-1108
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Volume19
Issue number7
DOIs
StatePublished - 23 May 2013
Externally publishedYes

Keywords

  • Information discovery
  • social data mining
  • social networks
  • social visualization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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