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Everyday the Same Picture: Popularity and Content Diversity

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Complex Networks VIII (CompleNet 2017)

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

Facebook is flooded by diverse and heterogeneous content, from kittens up to music and news, passing through satirical and funny stories. Each piece of that vivid production reflects the heterogeneity of the underlying social background and provides sometimes interesting opportunities for the study of social dynamics. Indeed, in Facebook we found an interesting case: a page having more than 40 K followers that every day posts the same picture of a popular Italian singer. We use such a peculiar page as a baseline for the study and modeling of the relationship between content heterogeneity and popularity. In particular, we perform a comparative analysis of information consumption patterns with respect to pages posting heterogeneous content (science and conspiracy news). We conclude the paper by introducing a model mimicking users selection preferences accounting for the heterogeneity of contents.

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Notes

  1. 1.

    We rescaled the number of likes to bring all values in the range [0, 1].

  2. 2.

    Note that we performed a unity–based normalization in order to bring all values of \(b \sim p\left( x\right) = x^{-1.5}\) in the range \(\left[ 0,1\right] \), so that the fixed–preference of the user is comparable with the attractiveness of the posts.

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Acknowledgements

Funding for this work was provided by EU FET project MULTIPLEX nr. 317532 and SIMPOL nr. 610704. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We want to thank Prof. Guido Caldarelli for precious insights and contribution on the data analysis. Special thanks to Josif Stalin, Stefano Alpi, Michele Degani for giving access to the Facebook page of La stessa foto di Toto Cutugno ogni giorno. Bruno Gonçalves thanks the Moore and Sloan Foundations for support as part of the Moore-Sloan Data Science Environment at NYU.

Author information

Authors and Affiliations

  1. Information Sciences Institute, University of Southern California, Los Angeles, California, USA

    Alessandro Bessi

  2. IMT Institute for Advanced Studies, Lucca, Italy

    Fabiana Zollo, Michela Del Vicario & Walter Quattrociocchi

  3. ISC CNR, Rome, Italy

    Antonio Scala

  4. Sapienza University of Rome, Rome, Italy

    Fabio Petroni

  5. Center for Data Science, New York University, New York, New York, USA

    Bruno Gonçcalves

Authors
  1. Alessandro Bessi
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  2. Fabiana Zollo
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  3. Michela Del Vicario
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  4. Antonio Scala
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  5. Fabio Petroni
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  6. Bruno Gonçcalves
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  7. Walter Quattrociocchi
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Correspondence to Bruno Gonçcalves .

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Editors and Affiliations

  1. New York University, Center for Data Science New York University, New York, New York, USA

    Bruno Gonçalves

  2. BioComplex Laboratory, School of Computing, Florida Institute of Technology, Melbourne, Florida, USA

    Ronaldo Menezes

  3. Center for Network Science and Mathematics Department, Central European University, Budapest, Hungary

    Roberta Sinatra

  4. Rudjer Bošković Institute, Theoretical Physics Division, Zagreb, Croatia

    Vinko Zlatic

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Bessi, A. et al. (2017). Everyday the Same Picture: Popularity and Content Diversity. In: Gonçalves, B., Menezes, R., Sinatra, R., Zlatic, V. (eds) Complex Networks VIII. CompleNet 2017. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-54241-6_20

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