The intertwined cyberbalkanizations of Facebook pages and their audience: an analysis of Facebook pages and their audience during the 2014 Hong Kong Occupy Movement


This study tests a hypothesis that information sources (e.g., Facebook pages) that share information more frequently with each other have high level of audience overlapping. This association is also hypothesized to be politically motivated. To test the empirical relationship, a Facebook pages sharing network was created using the information shared between 1453 Facebook pages during a social movement in Hong Kong. The sharing frequency between two pages was denoted as the page-level edge weight. The audience of Facebook pages—commenters and likers of the page’s posts—were collected. The Jaccard similarity coefficient between two pages was measured as the audience-level edge weight. Using network regression analysis, the page-level and audience-level edge weights were significantly associated. To show this relationship is politically motivated, 1076 audience members were randomly selected and with their political preferences labeled by inferring from their Facebook profile pictures. Using machine learning models, the repertoires of Facebook pages that they have interacted with can predict their political preferences. Our study demonstrated that selective sharing between information source is associated with the division of their audiences into enclaved subgroups with similar political ideologies.

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Fig. 1


  1. 1.

    Due to enclave deliberation, these isolated groups might develop more extreme views. However, the current study is not proposed to demonstrate this. For the effect of enclave deliberation on political polarization and how to avoid it, please refer to Strandberg, Himmelroos, & Grönlund [56].

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    Cambridge Dictionary:

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    We conducted a simulation study with simulated datasets. The two metrics (Phi and Jaccard) are highly correlated.

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    Suppose the audience size is 60,000 and, therefore, they have 17,999,700,000 dyads and 3.60 × 1016 triads. Suppose 500 triads can be computed per second, the whole triad census will take 2,283,094 years. As a reference, 2,283,094 years ago dates back to the middle old stone age when the species Homo sapiens did not exist.

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    The model tuning was performed with the R package caret.

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    The low recall (i.e., those with localism political ideology are wrongly classified as non-localism by the XGBoost model) for the prediction of localism political ideology might be explained by the Localist is a very heterogenous group of audience with different agendas and, therefore, they have different engagement patterns. Localists encompass a diverse range of users such as (1) autonomists, (2) pro-independent activists, (3) pro-democractic self-determination activists and (4) those who are disappointed by the old style of social movement and social administration.

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    The quote around “divide and conquer” is important because the meaning here is deviated from the original divide et impera in one significant way: the original meaning implies a mastermind (such as Julius Caesar) behind the division and ruling processes but the situation here is completely self-organized and self-imposed.







Engagement similarity


Audience overlapping


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This research project (Project Number: 2013.A8.009.14A) is funded by the Public Policy Research Funding Scheme of the Central Policy Unit of the Government of the Hong Kong Special Administrative Region. Part of the first author’s PhD studentship is supported by the HKU SPACE Postgraduate Fund.

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Conceived and designed: CHC, JYZ, KWF; data collection: CHC, JYZ, CSLC; data analysis: CHC, JYZ; manuscript preparation: CHC, JYZ, KWF; all authors read and approved the final manuscript

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Correspondence to Chung-hong Chan.

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Chan, Ch., Zhu, J.Y., Chow, C.Sl. et al. The intertwined cyberbalkanizations of Facebook pages and their audience: an analysis of Facebook pages and their audience during the 2014 Hong Kong Occupy Movement. J Comput Soc Sc 2, 183–205 (2019).

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  • Cyberbalkanization
  • Social media
  • Political polarization
  • Audience analysis