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Italian Workshop on Neural Nets

WIRN 2017 2017: Neural Advances in Processing Nonlinear Dynamic Signals pp 11–21Cite as

Temporal Artifacts from Edge Accumulation in Social Interaction Networks

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 102))

Abstract

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.

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Notes

  1. 1.

    https://llk.media.mit.edu/scratch-data.

  2. 2.

    http://konect.uni-koblenz.de/networks/facebook-wosn-wall.

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Acknowledgements

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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Authors and Affiliations

  1. George Mason University, Fairfax, VA, 22030, USA

    Matt Revelle, Carlotta Domeniconi & Aditya Johri

Authors
  1. Matt Revelle
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  2. Carlotta Domeniconi
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  3. Aditya Johri
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Corresponding author

Correspondence to Carlotta Domeniconi .

Editor information

Editors and Affiliations

  1. Dipartimento di Psicologia, Università della Campana Luigi Vanvitelli, Caserta, Italy

    Anna Esposito

  2. Fundació Tecnocampus, Pompeu Fabra University, Mataro, Barcelona, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Environmental, Energy, and Material Engineering, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Laboratorio di Neuronica, Dipartimento Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy

    Eros Pasero

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Revelle, M., Domeniconi, C., Johri, A. (2019). Temporal Artifacts from Edge Accumulation in Social Interaction Networks. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Advances in Processing Nonlinear Dynamic Signals. WIRN 2017 2017. Smart Innovation, Systems and Technologies, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-319-95098-3_2

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