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Negative influences of Facebook use through the lens of network analysis

Lien Faelens (UGent) , Kristof Hoorelbeke (UGent) , Eiko Fried, Rudi De Raedt (UGent) and Ernst Koster (UGent)
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Abstract
Various recent studies suggest a negative association between Facebook use and mental health. Yet, empirical evidence for this association is mixed, raising the question under which conditions Facebook use is related to negative outcomes, such as decreased well-being. Our study addresses this question by investigating the relationship between Facebook use, rumination, depressive, anxiety-, and stress-related symptoms, taking into account potential key variables such as social comparison, contingent self-esteem, and global self-esteem. In a first study, we explored the unique relations between these constructs using state-of-the-art network analysis. Subsequently, we conducted a preregistered replication study. In both studies, social comparison and self-esteem held a central position in the network, connecting social media use with indicators of psychopathology. These findings highlight the prominent role of social comparison and self-esteem in the context of social media use and well-being. Longitudinal and experimental studies will be required to further investigate these relationships.
Keywords
SOCIAL MEDIA USE, LOW SELF-ESTEEM, DEPRESSIVE SYMPTOMS, ANXIETY, USAGE, RUMINATION, STATES, SCALE, RISK, Social media, Self-esteem, Depression, Anxiety, Stress

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Please use this url to cite or link to this publication:

Chicago
Faelens, Lien, Kristof Hoorelbeke, Eiko Fried, Rudi De Raedt, and Ernst Koster. 2019. “Negative Influences of Facebook Use Through the Lens of Network Analysis.” Computers in Human Behavior 96: 13–22.
APA
Faelens, L., Hoorelbeke, K., Fried, E., De Raedt, R., & Koster, E. (2019). Negative influences of Facebook use through the lens of network analysis. COMPUTERS IN HUMAN BEHAVIOR, 96, 13–22.
Vancouver
1.
Faelens L, Hoorelbeke K, Fried E, De Raedt R, Koster E. Negative influences of Facebook use through the lens of network analysis. COMPUTERS IN HUMAN BEHAVIOR. Oxford: Pergamon-elsevier Science Ltd; 2019;96:13–22.
MLA
Faelens, Lien et al. “Negative Influences of Facebook Use Through the Lens of Network Analysis.” COMPUTERS IN HUMAN BEHAVIOR 96 (2019): 13–22. Print.
@article{8620047,
  abstract     = {Various recent studies suggest a negative association between Facebook use and mental health. Yet, empirical evidence for this association is mixed, raising the question under which conditions Facebook use is related to negative outcomes, such as decreased well-being. Our study addresses this question by investigating the relationship between Facebook use, rumination, depressive, anxiety-, and stress-related symptoms, taking into account potential key variables such as social comparison, contingent self-esteem, and global self-esteem. In a first study, we explored the unique relations between these constructs using state-of-the-art network analysis. Subsequently, we conducted a preregistered replication study. In both studies, social comparison and self-esteem held a central position in the network, connecting social media use with indicators of psychopathology. These findings highlight the prominent role of social comparison and self-esteem in the context of social media use and well-being. Longitudinal and experimental studies will be required to further investigate these relationships.},
  author       = {Faelens, Lien and Hoorelbeke, Kristof and Fried, Eiko and De Raedt, Rudi and Koster, Ernst},
  issn         = {0747-5632},
  journal      = {COMPUTERS IN HUMAN BEHAVIOR},
  keywords     = {SOCIAL MEDIA USE,LOW SELF-ESTEEM,DEPRESSIVE SYMPTOMS,ANXIETY,USAGE,RUMINATION,STATES,SCALE,RISK,Social media,Self-esteem,Depression,Anxiety,Stress},
  language     = {eng},
  pages        = {13--22},
  publisher    = {Pergamon-elsevier Science Ltd},
  title        = {Negative influences of Facebook use through the lens of network analysis},
  url          = {http://dx.doi.org/10.1016/j.chb.2019.02.002},
  volume       = {96},
  year         = {2019},
}

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