##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Apr 28, 2023

Qing Zhang  

Xiujuan Meng

Abstract

The introduction of new media has accelerated changes in the generation and delivery of information. Cyberemotions, as a new type of public opinion, can be more contagious and propagate in more diverse ways than traditional public sentiments. The emotions of internet users have a rising influence on the progression of recent significant social events. In order to spark additional discussion on online sentiment modulation and online public opinion tracking, this article presented an overview of cyberemotions definition and key analytical methodologies in existing online sentiment research, as well as a synopsis of major components of cyberemotions.

##plugins.themes.bootstrap3.article.details##

Keywords

Cyberemotions, The Era of New Media, Online Emotion Regulation

Supporting Agencies

This study is supported by the project of Research on the Effect of Online Emotion Regulation on Adolescent Mental Health (B/2022/01/161), a key project of Jiangsu Province’s Education Science Planning.

References
1. Holyst JA (eds.). Cyberemotions: Collective Emotions in Cyberspace. Springer International Publishing Switzerl. 2017.

2. Bi QL. Online emotion reactions to social events: The role of media framework. Southeast Comm 2019; 2019(6):72-75. DOI: https://doi.org/10.13556/j.cnki.dncb.cn35-1274/j.2019.06.024

3. CNNIC. The 51st Statistical Report on China’s Internet Development. China Internet Network Information Center. (2023-03-02). Available at: https://cnnic.cn/NMediaFile/2023/0322/MAIN16794576367190GBA2HA1KQ.pdf

4. Ahn J, Borowiec A, Buckley K, Cai D, Chmiel A, Czaplicka A, Dąbrowski G, Garas A, Garcia D, Gobron S, Hillmann R, Hołyst J, Kappas A, Küster D, Mitrovic M, Paltoglou G, Pirker H, Rank S, Schweitzer F, Sienkiewicz J, Skowron M, Sobkowicz P, Thalmann D, Thelwall M, Theunis M, Trier M, Tsankova E, Weronski P. CYBEREMOTIONS – Collective Emotions in Cyberspace. Procedia Comput Sci 2011; 7:221-222. DOI: https://doi.org/10.1016/j.procs.2011.09.076

5. Tang C. An empirical study on the evolution of cyber emotions. J Intellig 2012; 31(10):48-52.

6. Zhang M. Research on network sentiment and humanities education of universities. World Scientific Publishing. Proceedings of the 2016 Asia-Pacific English Language Teaching Conference. 2016.

7. Zhou L, Cai L & Liu Y. Cultural differences in cyber sentiments: An analysis of online emotion reactions of the four nations on YouTube to the November 13th Paris Terrorist Attack. J Intellig 2017; 2017(3):61-66.

8. Xu L, Wang QJ. Social and cultural Attributions and factors influencing online emotion expressions in hot sports incidents: A case study of Sun Yang’s Doping Penalty in 2020. Sport Sci 2021; 2021(6):103-110. DOI: https://doi.org/10.13598/j.issn1004-4590.2021.06.015

9. Sobkowicz P, Sobkowicz A. Two-year study of emotion and communication patterns in a highly polarized political discussion forum. Soc Sci Comput Rev 2012; 30(4):448-469. DOI: http://dx.doi.org/10.1177/0894439312436512

10. Ye YH, Xu Y, Zhu YJ. The characteristics of internet users’ moral emotions at the “man-made misfortune”: A study based on big data from Weibo. J Psychol 2016; 48(3):290-304.

11. Le GA, Dong YH, Chen H, Lai KS. Emotion analysis technology for online texts and application. Adv Psychol Sci 2013; 21(10):1711-1719.

12. Russell JA. A circumplex model of affect. Journal of Personality and Social Psychology 1980;39(06):1161-1178. DOI: http://dx.doi.org/10.1037/h0077714

13. Watson D, Tellegen A. Toward a consensual structure of mood. Psychol Bull 1985; 98(2):219-235. DOI: https://doi.org/10.1037/0033-2909.98.2.219

14. Raghavan M, Poongavanam MK, Ramachandran SR, Sridhar R. Emotion and sarcasm identification of posts from Facebook data using a hybrid approach. ICTACT J Soft Comput 2017; 7(2):1427-1435. DOI: http://doi.org/10.21917/ijsc.2017.0197

15. Lu H. An analysis of online emotional communication. News Window 2018; 2018(4):67

16. Smith ER, Seger CR, Mackie DM. Can emotions be truly group level? Evidence regarding four conceptual criteria. J Personal Soc Psychol 2007;93(3):431-446. DOI: https://doi.org/10.1037/0022-3514.93.3.431

17. Wang Y. A brief analysis of the polarization of online groups. News World 2011; 2011(6):100-101.

18. Medhat W, Hassan A, Korashy H. Sentiment analysis algorithms and applications: A survey. Ain Shams Eng J 2014; 2014(5):1093-1113. DOI: https://doi.org/10.1016/j.asej.2014.04.011

19. Zhao N, Jiao D, Bai S, Zhu T. Evaluating the validity of simplified Chinese version of LIWC in detecting psychological expressions in short texts on social network services. Plos One 2016; 11(6):1-15.

20. Khan FH, Bashir S, Qamar U. TOM: Twitter opinion mining framework using hybrid classification scheme. Decis Support Syst 2014; 57:245-257.

21. Morency LP, Mihalcea R, Doshi P. Towards Multimodal Sentiment Analysis: Harvesting Opinions from the Web. Proceedings of International Conference on Multimodal Interfaces. 2011.

22. Wu LQ, Zhang D, Li SS, Chen Y. A multimodal emotion recognition approach based on multitask learning. Computer Science 2019; 2019(11):284-290.

23. Golder SA, Macy MW. Diurnal and season mood vary with work, sleep, and daylength across diverse cultures. Science 2011; 333(6051):1878-1881. DOI: https://doi.org/10.1126/science.1202775

24. Derks D, Fischer AH, Bos AER. The role of emotion in computer-mediated communication: A review. Comput Human Behav 2007; 24(3)766-785. DOI: https://doi.org/10.1016/j.chb.2007.04.004

25. Tang Y, Hew K. Emoticon, emoji, and sticker use in computer-mediated communications: Understanding its communicative function, impact, user behavior, and motive. Educational Communications and Technology Yearbook 2018. pp.191-201.

26. Ahmad T, Ramsay A, Ahmed H. Detecting emotions in English and Arabic tweets. Information 2019; 10(3):98-118. DOI: https://doi.org/10.3390/info10030098

27. Xu YT, Lin Y. The mechanism of live streaming marketing for driving consumer behavior: A new perspective of immersive communication, physical media, and emotional involvement. Fujian Tribune, 2021; 2021(12):111-117.

28. Xiao W, Hou JQ. The relationship between emotional intelligence and internet addiction among vocational college students: The mediating effect of social support. Chin J Special Educ 2017; 2017(10):56-62.

29. Slonje R, Smith PK, Frisén A. The nature of cyberbullying, and strategies for prevention. Comput Human Behav 2013; 29(1):26-32. DOI: https://doi.org/10.1016/j.chb.2012.05.024

30. Feng JJ. Cyber bullying and prevention education. Res Educ Develop 2018; 38(12):49-54.

31. Fu TT, Li P, Ye T. Empathy and cyberbullying: A chain mediation model. Psychology: Techniq Applic 2020; 2020(02):104-113.

32. Yudes C, Rey L, Extremera N. The moderating effect of emotional intelligence on problematic internet use and cyberbullying perpetration among adolescents: Gender differences. Psychol Rep 2022;125(6):2902-2921. DOI: https://doi.org/10.1177/00332941211031792

33. Jiang JG, Li YX. Online emotion expressions and guidance on values: Reflections on “Sang” culture. Changbai J 2018; 2018(6):143-151.

34. Wood MA, Bukowski WM, Lis E. The digital self: How social media serves as a setting that shapes youth’s emotional experiences. Adol Res Rev 2016; 1(2):163-173. DOI: https://doi.org/10.1007/S40894-015-0014-8
How to Cite
Zhang, Q., & Meng, X. (2023). Cyberemotions in the Era of New Media. Science Insights, 42(4), 885–890. https://doi.org/10.15354/si.23.re277
Section
Review