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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Sep 7, 2025
Date Accepted: Feb 17, 2026

The final, peer-reviewed published version of this preprint can be found here:

Emotion Expression in Breast Cancer Support Seeking: Empirical Study of an Online Community

Xu A, Aljanaideh A, Xu J, Hao H

Emotion Expression in Breast Cancer Support Seeking: Empirical Study of an Online Community

JMIR Med Inform 2026;14:e83674

DOI: 10.2196/83674

PMID: 41973505

PMCID: 13122135

Emotion Expression in Breast Cancer Support Seeking: An Empirical Study of an Online Community

  • Anqi Xu; 
  • Ahmad Aljanaideh; 
  • Jennifer Xu; 
  • Haijing Hao

ABSTRACT

Background:

Breast cancer affects millions of women and presents not only medical challenges but also emotional, financial, and social burdens. Beyond clinical treatment, patients increasingly turn to online cancer communities (OCCs) for informational support, emotional support, and shared coping strategies. OCCs help patients manage daily life and reduce psychological distress through shared experiences and empathetic engagement.

Objective:

This study explores how emotions expressed in patients’ initial posts affect community engagement in OCCs. Using Plutchik’s emotional framework, it investigates whether different emotions lead to distinct patterns of member response, which offers insights into the emotional dynamics of peer support in digital health environments.

Methods:

This study leverages Plutchik’s Wheel of Emotions to explore how the eight primary emotions expressed in an initial post - surprise, anticipation, joy, sadness, trust, disgust, fear, and anger -distinctively influence responses of members in OCCs. We collect data from a breast cancer community, extract emotion scores from initial posts with Bidirectional Encoder Representations from Transformers (BERT), gauge the community responses in four categories, and empirically analyze the effects of different emotions on user response behavior.

Results:

The analysis results show that some emotions, e.g., joy, sadness, anticipation, and anger, consistently elicit stronger responses across all measured categories, and for most pairs of opposite emotions (e.g., surprise versus anticipation, joy versus sadness, and anger versus fear), the impacts on the four types of community responses move in parallel directions rather than opposite ones.

Conclusions:

Our study is the first to analyze how different expressed emotions in initial posts impact community engagement. The findings of this study provide future researcher a new perspective of understanding emotions, enhance our understanding of community dynamics in OCCs, and offer valuable implications for researchers, OCC facilitators, and medical professionals in supporting patients within these digital platforms.


 Citation

Please cite as:

Xu A, Aljanaideh A, Xu J, Hao H

Emotion Expression in Breast Cancer Support Seeking: Empirical Study of an Online Community

JMIR Med Inform 2026;14:e83674

DOI: 10.2196/83674

PMID: 41973505

PMCID: 13122135

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