Bursting the filter bubble: the mediating effect of discussion frequency on network heterogeneity

Nadine Strauß, Laura Alonso-Muñoz, Homero Gil de Zúñiga

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Purpose: The purpose of this study is to identify the structural processes that lead citizens to escape their common social circles when talking about politics and public affairs (e.g. “filter bubbles”). To do so, this study tests to what extent political attitudes, political behavior, news media consumption and discussion frequency affect discussion network heterogeneity among US citizens. Design/methodology/approach: Supported by the polling group Nielsen, this study uses a two-wave panel online survey to study the antecedents and mechanisms of discussion network heterogeneity among US citizens. To test the hypotheses and answer the research questions, ordinary least squares (OLS) regressions (cross-sectional, lagged and autoregressive) and mediation analyses were conducted. Findings: The findings imply that political discussion frequency functions as the key element in explaining the mechanism that leads politically interested and participatory citizens (online) as well as news consumers of traditional and online media to seek a more heterogeneous discussion network, disrupting the so-called “filter bubbles.” However, mediation analyses also showed that discussion frequency can lead to more homogenous discussion networks if people score high on political knowledge, possibly reflecting the formation of a close network of political-savvy individuals. Originality/value: The survey data give important insights into the 2016 pre-election situation, trying to explain why US citizens were more likely to remain in homogenous discussion networks when talking about politics and public affairs. By using two-wave panel data, the analyses allow to draw tentative conclusions about the influential and inhibiting factors and mechanisms that lead individuals to seek/avoid a more heterogeneous discussion network.

Original languageEnglish (US)
Pages (from-to)1161-1181
Number of pages21
JournalOnline Information Review
Issue number6
StatePublished - Oct 23 2020

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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