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Facebook wall posts: a model of user behaviors

Social Network Analysis and Mining volume 7, Article number: 6 (2017) Cite this article

Abstract

How do people interact with their Facebook wall? At a high level, this question captures the essence of our work. While most prior efforts focus on Twitter, the much fewer Facebook studies focus on the friendship graph or are limited by the amount of users or the duration of the study. In this work, we model Facebook user behavior: we analyze the wall activities of users focusing on identifying common patterns and surprising phenomena. We conduct an extensive study of roughly 7k users over 3 years during 4-month intervals each year. We propose PowerWall, a lesser known heavy-tailed distribution to fit our data. Our key results can be summarized in the following points. First, we find that many wall activities, including number of posts, number of likes, number of posts of type photo, can be described by the PowerWall distribution. What is more surprising is that most of these distributions have similar slope, with a value close to 1! Second, we show how our patterns and metrics can help us spot surprising behaviors and anomalies. For example, we find a user posting every two days, exactly the same count of posts; another user posting at midnight, with no other activity before or after. Our work provides a solid step toward a systematic and quantitative wall-centric profiling of Facebook user activity.

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Notes

  1. https://www.facebook.com.

  2. http://www.json.org/.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under Grants Nos. SaTC 1314935, IIS-1217559, CNS-1314632, IIS-1408924, by DARPA Grant Social Media in Strategic Communication (SMISC) program under Agreement Number W911NF-12-C-0028 and by the Army Research Laboratory under Cooperative Agreement Number W911NF-09-2-0053. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or other funding parties. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.

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Authors and Affiliations

  1. Department of Computer Science, Bourns School of Engineering, University of California, Riverside, CA, USA

    Pravallika Devineni & Michalis Faloutsos

  2. Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA

    Danai Koutra

  3. Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

    Christos Faloutsos

Authors
  1. Pravallika Devineni
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  2. Danai Koutra
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  3. Michalis Faloutsos
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  4. Christos Faloutsos
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Correspondence to Pravallika Devineni.

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Devineni, P., Koutra, D., Faloutsos, M. et al. Facebook wall posts: a model of user behaviors. Soc. Netw. Anal. Min. 7, 6 (2017). https://doi.org/10.1007/s13278-017-0422-9

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  • DOI: https://doi.org/10.1007/s13278-017-0422-9

Keywords

  • Heavy-tailed distributions
  • Power law
  • Social networks
  • Facebook
  • User behavior
  • Statistical modeling