Visual social network analytics for relationship discovery in the enterprise

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

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

25 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 also provide details of a 12-month-long, large-scale deployment to almost 1,800 users from which we 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
Title of host publicationVAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings
Pages71-79
Number of pages9
DOIs
StatePublished - 1 Dec 2011
Externally publishedYes
Event2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011 - Providence, RI, United States
Duration: 23 Oct 201128 Oct 2011

Publication series

NameVAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings

Conference

Conference2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011
Country/TerritoryUnited States
CityProvidence, RI
Period23/10/1128/10/11

Keywords

  • information discovery
  • social data mining
  • social networks
  • social visualization

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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