The effect of graph layout on inference from social network data

  • Jim Blythe
  • Cathleen McGrath
  • David Krackhardt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1027)


Social network analysis uses techniques from graph theory to analyze the structure of relationships among social actors such as individuals or groups. We investigate the effect of the layout of a social network on the inferences drawn by observers about the number of social groupings evident and the centrality of various actors in the network. We conducted an experiment in which eighty subjects provided answers about three drawings. The subjects were not told that the drawings were chosen from five different layouts of the same graph. We found that the layout has a significant effect on their inferences and present some initial results about the way certain Euclidean features will affect perceptions of structural features of the network. There is no “best” layout for a social network; when layouts are designed one must take into account the most important features of the network to be presented as well as the network itself.


Social Network Degree Centrality Social Network Analysis Betweenness Centrality Social Network Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Jim Blythe
    • 1
  • Cathleen McGrath
    • 2
  • David Krackhardt
    • 2
  1. 1.School of Computer ScienceCarnegie Mellon UniversityPittsburgh
  2. 2.Heinz School of Public Policy and ManagementCarnegie Mellon UniversityUSA

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