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Personal Network Composition and Cognitive Reflection Predict Susceptibility to Different Types of Misinformation Cover

Personal Network Composition and Cognitive Reflection Predict Susceptibility to Different Types of Misinformation

Open Access
|Jun 2024

Figures & Tables

Figure 1:

Increased political network homogeneity predicts higher belief in political rumor.
Increased political network homogeneity predicts higher belief in political rumor.

Figure 2:

Republican network homogeneity predicts belief in conservative fake news.
Republican network homogeneity predicts belief in conservative fake news.

Figure 3:

Higher cognitive reflection predicts lower belief in conservative fake news in Republicans.
Higher cognitive reflection predicts lower belief in conservative fake news in Republicans.

Summary of hypotheses results_

HypothesisResult
H1: Homogeneity increases importance of political identity.
H2: Homogeneity increases ingroup evaluation.
H3a: Homogeneity increases political rumor bias.PS: Only for helping rumor
H3b: Homogeneity increases sharing political rumor bias.PS: Only for helping rumor
H4a: Homogeneity increases fake headline bias.PS: Only for Republicans
H4b: Homogeneity increases sharing fake headline bias.PS: Only for Republicans
H5a: Cognitive reflection not related to rumor belief.
H5b: Cognitive reflection not related to rumor sharing.
H6a: Cognitive reflection predicts fake news belief.PS: Only for Republicans
H6b: Cognitive reflection predicts fake news sharing.PS: Only for Republicans

Hypothesis summary list_

Hypothesis
H1: Homogeneity increases importance of political identity.
H2: Homogeneity increases ingroup evaluation.
H3a: Homogeneity increases political rumor bias.
H3b: Homogeneity increases sharing political rumor bias.
H4a: Homogeneity increases fake headline bias.
H4b: Homogeneity increases sharing fake headline bias.
H5a: Cognitive reflection not related to rumor belief.
H5b: Cognitive reflection not related to rumor sharing.
H6a: Cognitive reflection predicts fake news belief.
H6b: Cognitive reflection predicts fake news sharing.

The influence of network homogeneity on fake news headlines (Democrats and Republicans)_

Liberal fake newsShare liberal fake newsConservative fake newsShare conservative fake news
Network homogeneity−0.257 (−1.19)0.147 (0.54)0.465~1.690.012 (0.04)
Number of alters0.07 (0.99)0.078 (0.88)0.001 (0.01)−0.116 (−1.23)
Higher liberalism0.075 (1.36)0.024 (0.35)−0.168* (−2.14)−0.064 (−0.74)
Constant3.52** (5.67)2.55** (3.25)4.064 (7.43)3.48** (5.70)
N107107107107

The influence of network homogeneity on political rumor likelihood and sharing_

Ingroup helping rumor beliefOutgroup bullying rumor beliefShare ingroup helping rumorShare outgroup bullying rumor
Network homogeneity0.191~(1.74)0.055 (0.47)0.256* (2.52)0.081 (0.72)
Number of alters−0.001 (−0.02)0.007 (0.20)0.037 (1.15)−0.005 (−0.14)
Higher liberalism−0.034 (−1.18)−0.021 (−0.66)−0.059* (−2.17)−0.064 (−2.14)
Democrat identification0.133 (0.73)0.289 (1.46)0.201 (1.19)0.359~(1.92)
Constant0.614** (2.75)0.453~(1.88)0.288 (1.39)0.670** (2.93)
N214214214214

Homogeneity predicts political identity importance_

Political identity importance
Network homogeneity0.527** (3.28)
Number of alters0.011 (0.23)
Higher liberalism0.038 (0.89)
Democrat identification0.214 (0.80)
Constant2.392** (7.32)
N214

The influence of network homogeneity on political group ratings_

Ingroup evaluationOutgroup evaluation
Network homogeneity0.581** (2.69)−0.670** (−2.61)
Number of alters0.105 (1.53)0.035 (0.43)
Higher liberalism−0.096~(1.66)−0.058 (−0.84)
Democrat identification0.625~(1.74)−0.286 (−0.67)
Constant1.295** (2.95)−0.931~(−1.78)
N214214

Cognitive reflection predicts fake news headline belief in Republicans_

Liberal fake newsShare liberal fake newsConservative fake newsShare conservative fake news
CRT scores−0.026 (−0.46)−0.083 (−1.15)−0.115~(−1.82)−0.040 (−0.57)
Higher liberalism0.068 (1.23)0.038 (0.56)−0.190* (−2.44)−0.077 (−0.88)
Constant3.90 (7.44)3.20 (4.90)4.72**3.11
11.957.00
N107107107107

Cognitive reflection does not predict political rumors likelihood_

Ingroup helping rumorOutgroup bullying rumorShare ingroup helping rumorShare outgroup bullying rumor
CRT scores−0.19 (−0.71)−0.011 (−0.37)0.020 (0.79)0.016 (0.59)
Higher liberalism−0.012 (−0.76)0.019 (1.06)−0.029~(−1.86)−0.165 (−0.97)
Constant0.690 (4.69)0.443 (2.80)**0.411** (2.98)0.495 (3.28)
N214214214214
DOI: https://doi.org/10.21307/connections-2019.044 | Journal eISSN: 2816-4245 | Journal ISSN: 0226-1766
Language: English
Page range: 165 - 180
Published on: Jun 28, 2024
Published by: International Network for Social Network Analysis (INSNA)
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 Matthew Facciani, Cecilie Steenbuch-Traberg, published by International Network for Social Network Analysis (INSNA)
This work is licensed under the Creative Commons Attribution 4.0 License.