Emotional selection (information)

Emotional selection describes the perpetuation and evolution of information based on its ability to evoke emotions.[1][2] The hypothesis posits that information spreads throughout populations not just based on their factual accuracy or utility, but also based on the emotional impact it has on recipients.

Overview

Emotional selection suggests that if a meme or a piece of information evokes strong emotions—whether positive or negative—it is more likely to be shared and propagated. The emotional response effectively acts as a selection mechanism, giving certain memes an advantage in the competition for attention and dissemination. This hypothesis underscores the importance of emotional resonance in the virality and longevity of information in cultural evolution.

Additionally researchers have developed coupled models that treat emotion and information as two interacting propagation processes in social media. Instead of tracking "information spread," these models examine how group emotions influence information thresholds and diffusion patterns. They found that group emotional atmosphere influences how quickly and how far information is spread and that positive or neutral emotions often become dominant over negative ones. Additionally, they found that denser networks intensify emotional differences during the spread.[3] Additional study on this topic has revealed emotional responses themselves can also predict how content spreads. High-arousal and positive emotional reactions correlated with stronger moral contagion and real-time emotional measures outperform self-reports in predicting spread.[4]

Researchers of social media are now using epidemic models (the same disease spread kind) to include emotional contagion dynamics. These models divide exposed platform-users into positive, negative, and neutral emotional states and simulate how each emotional state evolves alongside information. This research discovered that the emotional responses of "key opinion leaders" have disproportional effects on information flow and group emotional states.[5]

A study from late 2025 on emotional diffusion found that following "high-impact events" (they used celebrity suicides as the main one) specific emotions influenced different spread metrics such as: size, speed, and burstiness. The emotion of disgust caused things to spread widely and rapidly, anger and surprise showed high initial burst but short "lifetimes" (how long it remained relevant), and joy tended to have a longer "lifetime". This further proves that emotional patterns shape how information propagates.[6]

A 2024 study on the influence of emotional factors of social media users on their information sharing behaviors during crisis found that positive emotions influenced information sharing more strongly than cognition alone and that one's emotional state acts as a "mediator" between their thoughts and whether or not they will share something online. This effects their decision making framework, not just diffusion.[7]

A study conducted on the COVID-19 pandemic showed that misinformation spread is also tied closely to the emotional contagion process, revealing that certain group dynamics and "bad actors" use this to shape the propagation of their misinformation during crises.[8]

References

  1. ↑ Heath, Chip; Bell, Chris; Sternberg, Emily (2001). "Emotional selection in memes: The case of urban legends". Journal of Personality and Social Psychology. 81 (6): 1028–1041. doi:10.1037/0022-3514.81.6.1028. PMID 11761305.
  2. ↑ Eriksson, Kimmo; Coultas, Julie C.; de Barra, Mícheál (24 February 2016). "Cross-Cultural Differences in Emotional Selection on Transmission of Information". Journal of Cognition and Culture. 16 (1–2): 122–143. doi:10.1163/15685373-12342171.
  3. ↑ Yan, Guanghui; Zhang, Xiaolong; Pei, Huayan; Li, Yuyao (2024-11-01). "An emotion-information spreading model in social media on multiplex networks". Communications in Nonlinear Science and Numerical Simulation. 138 108251. Bibcode:2024CNSNS.13808251Y. doi:10.1016/j.cnsns.2024.108251. ISSN 1007-5704.
  4. ↑ Li, Rui; Liu, Xu; Yu, Yipeng; Su, Waxun; Hu, Yueqin (2026-01-01). "Beyond content: Multimodal emotional responses predict online moral contagion across laboratory and real-world contexts". International Journal of Human-Computer Studies. 208 103689. doi:10.1016/j.ijhcs.2025.103689. ISSN 1071-5819.
  5. ↑ Chen, Hejie; Jin, Jiamin; Sun, Steven; Zhang, Chuyi; Yu, Minshan (2025-07-22). "Research on propagation dynamics of emotional contagion using S3EIR model based on multiple social media platforms". Frontiers in Communication. 10 1582974. doi:10.3389/fcomm.2025.1582974. ISSN 2297-900X.
  6. ↑ Nouri, Ehsan; Saraf, Nilesh; Goh, Jie Mein; Dasgupta, Srabana; Cyr, Dianne (2025). "Online propagation of emotions: A study of resharing dynamics on social media following celebrity suicides". PLOS ONE. 20 (12) e0336134. Bibcode:2025PLoSO..2036134N. doi:10.1371/journal.pone.0336134. ISSN 1932-6203. PMC 12694876. PMID 41370280.
  7. ↑ Yanxia, Lu (12 June 2024). "The Influence of Cognitive and Emotional Factors on Social Media Users' Information-Sharing Behaviours during Crises: The Moderating Role of the Construal Level and the Mediating Role of the Emotional Response". Behavioral Sciences. 14 (6). doi:10.3390/b (inactive 19 May 2026). ISSN 2076-328X. Archived from the original on 2025-04-20.{{cite journal}}: CS1 maint: DOI inactive as of May 2026 (link)
  8. ↑ Chen, Qiuyi; Liu, Qian (2025). "Unveiling emotional contagion in COVID-19 misinformation: Computational analysis for public health crisis surveillance". Health Informatics Journal. 31 (4) 14604582251381175. doi:10.1177/14604582251381175. ISSN 1741-2811. PMID 41042280.