Beyond friendship: modeling user activity graphs on social network-based gifting applications

  • Authors:

  • Atif Nazir;Alex Waagen;Vikram S. Vijayaraghavan;Chen-Nee Chuah;Raissa M. D'Souza;Balachander Krishnamurthy

  • Affiliations:

  • University of California--Davis, Davis, California, USA;University of California--Davis, Davis, California, USA;University of California--Davis, Davis, California, USA;University of California--Davis, Davis, California, USA;University of California--Davis, Davis, California, USA;AT&T Labs--Research, Florham Park, New Jersey, USA

  • Venue:
  • Proceedings of the 2012 ACM conference on Internet measurement conference
  • Year:
  • 2012

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Abstract

We employ user activity data from three highly popular gifting applications on Facebook to study the evolution of user activity on applications through the most commonly-used growth mechanism, namely Application Requests. We find user activity graphs differ from friendship graphs in large part due to the inherent directionality of user activity, and node transience. Our results show that, unlike degree distributions in friendship graphs, activity graphs exhibit strong asymmetry in in- and out-degree distributions, and that out-degrees are not accurately described by currently known parametric distributions. As such, user activity graphs cannot be simulated through existing intent- and feature-driven algorithms that can model friendship graphs. We present a novel probabilistic growth model for user activity on the gifting genre of social applications. Our model decouples in- and out-degrees based on their distinct nature exhibited by our empirical data. We use the insight that regardless of increasing, declining or stable user activity, gifting application user activity exhibits the same graph structure. Our model produces synthetic graphs that consist of disconnected components with low clustering of nodes, and exhibit degree structures very similar to our real activity data. We discuss the benefits and shortfalls of our model and its applicability to other types of OSN-based applications, such as social games. To the best of our knowledge this study is the first to explore and model user activity growth processes on OSN-based applications.