Temporal Artifacts from Edge Accumulation in Social Interaction Networks

  • Matt Revelle
  • Carlotta DomeniconiEmail author
  • Aditya Johri
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 102)


There has been extensive research on social networks and methods for specific tasks such as: community detection, link prediction, and tracing information cascades; and a recent emphasis on using temporal dynamics of social networks to improve method performance. The underlying models are based on structural properties of the network, some of which we believe to be artifacts introduced from common misrepresentations of social networks. Specifically, representing a social network or series of social networks as an accumulation of network snapshots is problematic. In this paper, we use datasets with timestamped interactions to demonstrate how cumulative graphs differ from activity-based graphs and may introduce temporal artifacts.



We appreciate the Lifelong Kindergarten group at MIT for publicly sharing the Scratch datasets. This work is partly based upon research supported by U.S. National Science Foundation (NSF) Awards DUE-1444277 and EEC-1408674. Any opinions, recommendations, findings, or conclusions expressed in this material are those of the authors and do not necessarily reflect the views of NSF.


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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Matt Revelle
    • 1
  • Carlotta Domeniconi
    • 1
    Email author
  • Aditya Johri
    • 1
  1. 1.George Mason UniversityFairfaxUSA

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