Cyberpsychology: Journal of Psychosocial Research on Cyberpspace (Sep 2022)

The effect of emotion background on pathological internet users’ comments on online news: Evidence from online text analysis

  • Wei Zhang,
  • Wanling Zhu,
  • Jia Nie,
  • Frank Andrasik,
  • Xara Naomi Blom

DOI
https://doi.org/10.5817/CP2022-4-8
Journal volume & issue
Vol. 16, no. 4

Abstract

Read online

The increased use of Internet communication emphasizes the need to explore the characteristics of online comments, which help better understand their impact on individuals’ internal emotional states and how the emotional valence of online news impacts online commentaries among Pathological Internet Users (PIUs). Eighteen PIUs and 14 controls commented on online news of two types (positive and negative valence) under two separate elicited emotional states (positive and negative), with commentaries analyzed through TextMind. PIUs and Controls both used more positive words when exposed to positive versus negative news and more negative words when exposed to negative versus positive news regardless of elicited emotions. However, individuals with PIU used more positive words than controls. PIUs and Controls commented similarly under positive or negative emotion elicitation concerning casual, inclusive, and exclusive words. However, the use of discrepancy word varied due to group assignment and the emotion background. Controls used more discrepancy words when commenting on negative news while in a positive emotional state and commenting on positive news while in a negative emotional state, which does not hold for PIUs. The internal emotional state and emotional valence of online news affected the group differently, suggesting that though PIUs can get emotional catharsis on commenting activities, they lack the perceptual consistency of emotional background when conducting online activities and have lower cognitive complexity. This research demonstrates the utility of incorporating a new method for detecting individuals subject to PIU by applying text analysis to their online behavior.

Keywords