Education, Science, Technology, Innovation and Life
Open Access
Sign In

The Implication of Negative Emotional Comments on the Evolution of Online Public Opinion: Exampled with Sina Weibo

Download as PDF

DOI: 10.23977/jsoce.2022.040808 | Downloads: 13 | Views: 531

Author(s)

Chao Yang 1

Affiliation(s)

1 State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China

Corresponding Author

Chao Yang

ABSTRACT

Negative comment messages tend to have stronger emotional energy among the Internet and have an important impact on the evolution of online public opinion. This study analyzes the influence of negative comments on individual perceptions and group emotions of Internet users based on the sample of comment discourse of events that are hotly searched on Sina Weibo. The results of the study show that the performance characteristics of negative comments differ for international news, social news, and entertainment discussion topics. Reviews of negative emotional attributes received more comments, rally more social sentiment and stimulate the transmission of sentiment. And negative emotion comments involving other events in the past can stimulate Internet users' memories and construct the collective memory of the Internet. The study facilitates the understanding of the impact of negative emotional comments on the cognitive psychology of Internet users in online public opinion and provides a reference for scientific understanding of online social psychology. 

KEYWORDS

Negative emotions, Online public opinion, Sina Weibo, Public pressure, Text analysis

CITE THIS PAPER

Chao Yang, The Implication of Negative Emotional Comments on the Evolution of Online Public Opinion: Exampled with Sina Weibo. Journal of Sociology and Ethnology (2022) Vol. 4: 41-54. DOI: http://dx.doi.org/10.23977/jsoce.2022.040808.

REFERENCES

[1] Rong, R., and Shu, R. A case study of Microblog opinion leaders and their public opinion expression in Tianjin "8•12" explosion accident based on SINA Weibo. News Research, 2017, (7), pp.7−10. 
[2] Fang, Y, Chen, X., Song, Z., Wang, T.Z., and Cao, Y. Modelling Propagation of Public Opinions on Microblogging Big Data Using Sentiment Analysis and Compartmental Models. International Journal on Semantic Web & Information Systems, 2017, 13(1), pp.11-27.
[3] Tadić, B., Šuvakov, M., Garcia, D., and Schweitzer, F. Agent-based simulations of emotional dialogs in the online social network myspace. Springer International Publishing, 2017, pp. 207−229. 
[4] Hua, W., Wu, S.Y., Yu, C., Wu, J.X., and X, J. The Analysis Method of Multi-layer Sentiment Divergence for Network Public Opinion Events. Data Analysis and Knowledge Discovery, 2022, 66(6), pp. 3-19.
[5] Zhang, M., Ding, S.H., Liu, G.F., Xu, Y.Z., Fu, X,Y., Zhang, W., and Xin, Z.Q. Negativity bias in emergent online events: Occurrence and manifestation, Acta Psychologica Sinica, 2021, 53(12), pp. 1362. 
[6] Yang, C. Z. Research of effect of information cascade on cognitive bias in network emergency. Journal of Intelligence, 2020, 39(2), pp. 116−123. 
[7] Prochazkova, E., and Kret, M. E. Connecting minds and sharing emotions through mimicry: A neurocognitive model of emotional contagion. Neuroscience & Biobehavioral Reviews, 2017, 80, pp. 99–114.
[8] Vanman, E. J. The role of empathy in intergroup relations. Current Opinion in Psychology, 2016, 11, pp.59–63. 
[9] Rhee, S. Y., Park, H., and Bae, J. Network structure of affective communication and shared emotion in teams. Behavioral Sciences, 2020, 10(10), pp.159. 
[10] Parkinson, B. Intragroup emotion convergence: Beyond contagion and social appraisal. Personality and Social Psychology Review, 2019, 24(2), pp. 121–140. 
[11] Liu, X., Chi, N., and Gremler, D. D. Emotion cycles in services: Emotional contagion and emotional labor effects. Journal of Service Research, 2019, 22(3), pp. 285–300. 
[12] Gabriel, S., Naidu, E., Paravati, E., Morrison, C. D., and Gainey, K. Creating the sacred from the profane: Collective effervescence and everyday activities. Journal of Positive Psychology, 2020, 15(1), pp. 129–154. 
[13] Stubbersfield, J. M., Flynn, E. G., and Tehrani, J. J. Chicken tumours and a fishy revenge: Evidence for emotional content bias in the cumulative recall of urban. legends. Journal of Cognition & Culture, 2017, 17(1-2), pp. 12−26. 
[14] Bebbington, K., MacLeod, C., Ellison, T. M., and Fay, N. The sky is falling: Evidence of a negativity bias in the social transmission of information. Evolution and Human Behavior, 2017, 38(1), pp.92–101. 
[15] An, L, Wu, L. An Integrated Analysis of Topical and Emotional Evolution of Microblog Public Opinions on Public Emergencies. Library and Information Service, 2017, 61(15), pp, 123-124.

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.