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Multiple leaders on a multilayer social media

Author

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  • Borondo, J.
  • Morales, A.J.
  • Benito, R.M.
  • Losada, J.C.

Abstract

Twitter is a social media platform where users can interact in three different ways: following, mentioning, or retweeting. Accordingly, one can define Twitter as a multilayer social network where each layer represents one of the three interaction mechanisms. First, we review the main findings of our previous work regarding two Twitter political conversations: the 2010 Venezuelan protest and the 2011 Spanish general elections. We found that the structure of the follower layer conditions the retweet layer, as having a low number of followers represents a constrain to effectively propagate information. The collapsed directed multiplex network does not present a rich-club ordering, as politicians presided large communities of regular users in the mention layer; while media accounts were the sources from which people retweeted information. However, when considering reciprocal interactions the rich-club ordering emerges, as elite accounts preferentially interacted among themselves and largely ignored the crowd. Finally, we explore the main relationships between the community structure of the three layers. At the follower level users cluster in large and dense communities holding various hubs, that break into smaller and more segregated ones in the mention and retweet layers. Hence, we argue that to fully understand Twitter we have to analyze it as a multilayer social network, evaluating the three types of interactions.

Suggested Citation

  • Borondo, J. & Morales, A.J. & Benito, R.M. & Losada, J.C., 2015. "Multiple leaders on a multilayer social media," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 90-98.
  • Handle: RePEc:eee:chsofr:v:72:y:2015:i:c:p:90-98
    DOI: 10.1016/j.chaos.2014.12.023
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    References listed on IDEAS

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    1. Morales, A.J. & Losada, J.C. & Benito, R.M., 2012. "Users structure and behavior on an online social network during a political protest," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5244-5253.
    2. Wu, Fang & Huberman, Bernardo A. & Adamic, Lada A. & Tyler, Joshua R., 2004. "Information flow in social groups," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 327-335.
    3. Borondo, J. & Morales, A.J. & Benito, R.M. & Losada, J.C., 2014. "Mapping the online communication patterns of political conversations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 403-413.
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    Cited by:

    1. Martin-Gutierrez, Samuel & Losada, Juan C. & Benito, Rosa M., 2023. "Multipolar social systems: Measuring polarization beyond dichotomous contexts," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    2. G. Olivares & J. P. Cárdenas & J. C. Losada & J. Borondo, 2019. "Opinion Polarization during a Dichotomous Electoral Process," Complexity, Hindawi, vol. 2019, pages 1-9, February.
    3. S. Martin-Gutierrez & J. C. Losada & R. M. Benito, 2018. "Recurrent Patterns of User Behavior in Different Electoral Campaigns: A Twitter Analysis of the Spanish General Elections of 2015 and 2016," Complexity, Hindawi, vol. 2018, pages 1-15, December.
    4. Xiong, Xi & Li, Yuanyuan & Qiao, Shaojie & Han, Nan & Wu, Yue & Peng, Jing & Li, Binyong, 2018. "An emotional contagion model for heterogeneous social media with multiple behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 185-202.
    5. Liu, Yang & Wei, Bo & Du, Yuxian & Xiao, Fuyuan & Deng, Yong, 2016. "Identifying influential spreaders by weight degree centrality in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 1-7.

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