Exploring Engagement With EU News on Facebook: The Influence of Content Characteristics

Heidenreich, Tobias; Eisele, Olga; Watanabe, Kohei; Boomgaarden, Hajo G. Article — Published Version Exploring Engagement With EU News on Facebook: The Influence of Content Characteristics Politics and Governance Provided in Cooperation with: WZB Berlin Social Science Center Suggested Citation: Heidenreich, Tobias; Eisele, Olga; Watanabe, Kohei; Boomgaarden, Hajo G. (2022) : Exploring Engagement With EU News on Facebook: The Influence of Content Characteristics, Politics and Governance, ISSN 2183-2463, Cogitatio, Lisbon, Vol. 10, Iss. 1, pp. 121-132, https://doi.org/10.17645/pag.v10i1.4775 This Version is available at: https://hdl.handle.net/10419/250895 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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The search string used to retrieve articles for this study contains the words “eu, europäisch* union, europawahl*, europawahl*, europäisch* gerichtshof*, eugh*, europaparlament*, europa-parlament*, europäisch* parlament, europaspitzenkandidat*, europa-abgeordnete*, europaabgeordnete*, europa-politiker*, europapolitiker*, europäisch* kommiss*, europäisch* zentralbank*, ezb*, eurozone*, euro-zone*, euroland*, euro-land*, euroländer*, euro-länder*, euroraum*, euro-raum*, eurostaat*, euro-staat*, europäisch* gemeinschaftswährung*, europäisch* rat*, rat der eu*, europäisch* ebene, europäisch* rechnungshof*, europäisch* auswärtig* dienst*, europäisch* investitionsbank*, europol*, frontex*, europäisch* agentur*, eurogruppe*, eurorettungsschirm*, europäisch* rettungsschirm, brexit*”. Table A1. Estimated Fixed Effects Parameters for Different Types of User Engagement Reactions Shares Comments [95% Credibility Interval] [95% Credibility Interval] [95% Credibility Interval] Intercept 3.8 [2.93 4.61] 1.84 [0.97 2.65] 2.79 [1.79 3.81] Proximity (Reference Category: EU Level) EU Country -0.09 [-0.16 -0.01] 0.1 [0 0.2] -0.18 [-0.27 -0.08] Bordering Country -0.01 [-0.11 0.09] -0.02 [-0.16 0.11] -0.11 [-0.23 0.01] Austria 0.13 [0.03 0.24] 0.08 [-0.06 0.22] 0.29 [0.16 0.42] Conflict -0.27 [-0.32 -0.22] -0.57 [-0.63 -0.51] -0.01 [-0.07 0.05] Negativity 0.27 [0.2 0.34] 0.58 [0.48 0.67] -0.11 [-0.2 -0.02] Emotionality -0.04 [-0.1 0.01] -0.15 [-0.22 -0.08] 0.13 [0.06 0.2] Article length 0.03 [0.02 0.04] 0.03 [0.02 0.05] 0.04 [0.02 0.06] Group effects Outlet level 1.44 [0.94 2.27] 1.46 [0.96 2.3] 1.71 [1.12 2.7] NB shape parameter 0.67 [0.65 0.68] 0.42 [0.41 0.43] 0.45 [0.44 0.47] N 10,380 10,380 10,380 Notes: All parameters are estimated based on 4,000 MCMC posterior draws. Modes of parameter distributions and 95% CIs are reposted. Flat priors are used throughout, therefore parameter estimates are equivalent to MLE parameters. Politics and Governance 2 Table A2. Estimated Fixed Effects Parameters for Different Types of User Engagement Reactions Shares Comments [95% Credibility Interval] [95% Credibility Interval] [95% Credibility Interval] Intercept 3.52 [2.78 4.26] 1.57 [0.84 2.31] 2.71 [1.78 3.64] Proximity (Reference Category: EU Level) EU Country -0.04 [-0.11 0.03] 0.15 [0.06 0.24] -0.2 [-0.3 -0.11] Bordering Country 0 [-0.1 0.1] 0.1 [-0.02 0.23] -0.11 [-0.23 0.01] Austria 0.17 [0.07 0.27] 0.08 [-0.05 0.21] 0.31 [0.18 0.44] Conflict -0.2 [-0.25 -0.16] -0.5 [-0.55 -0.44] 0.05 [-0.01 0.11] Negativity 0.13 [0.06 0.19] 0.4 [0.31 0.48] -0.15 [-0.24 -0.06] Emotionality 0.09 [0.03 0.14] 0.01 [-0.05 0.07] 0.15 [0.09 0.22] Article length 0.04 [0.03 0.05] 0.03 [0.02 0.05] 0.04 [0.03 0.06] Group effects Outlet level 1.28 [0.85 2.01] 1.24 [0.8 1.95] 1.63 [1.08 2.55] NB shape parameter 0.75 [0.73 0.77] 0.49 [0.47 0.5] 0.47 [0.46 0.49] N 10,224 10,224 10,224 Notes: All parameters are estimated based on 4,000 MCMC posterior draws. Modes of parameter distributions and 95% CIs are reposted. Flat priors are used throughout, therefore parameter estimates are equivalent to MLE parameters. Politics and Governance 3 Figure A1. MCMC Trace plots and Posterior Parameter Densities (Model for Interactions). Trace plots show a good mixture of the Markov Chains. Posterior densities indicate that parameters are distributed roughly normally. Politics and Governance 4 Figure A2. MCMC Trace plots and Posterior Parameter Densities (Model for Shares). Trace plots show a good mixture of the Markov Chains. Posterior densities indicate that parameters are distributed roughly normally. Politics and Governance 5 Figure A3. MCMC Trace plots and Posterior Parameter Densities (Model for Comments). Trace plots show a good mixture of the Markov Chains. Posterior densities indicate that parameters are distributed roughly normally.