Trends of fear and anger on YouTube during the initial stage of the COVID-19 outbreak in South Korea.
Anger
COVID-19
Fear
Pandemic
Trends
YouTube
Journal
BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562
Informations de publication
Date de publication:
04 Jun 2024
04 Jun 2024
Historique:
received:
03
10
2023
accepted:
31
05
2024
medline:
5
6
2024
pubmed:
5
6
2024
entrez:
4
6
2024
Statut:
epublish
Résumé
The COVID-19 pandemic has been the most widespread and threatening health crisis experienced by the Korean society. Faced with an unprecedented threat to survival, society has been gripped by social fear and anger, questioning the culpability of this pandemic. This study explored the correlation between social cognitions and negative emotions and their changes in response to the severe events stemming from the COVID-19 pandemic in South Korea. The analysis was based on a cognitive-emotional model that links fear and anger to the social causes that trigger them and used discursive content from comments posted on YouTube's COVID-19-related videos. A total of 182,915 comments from 1,200 videos were collected between January and December 2020. We performed data analyses and visualizations using R, Netminer 4.0, and Gephi software and calculated Pearson's correlation coefficients between emotions. YouTube videos were analyzed for keywords indicating cognitive assessments of major events related to COVID-19 and keywords indicating negative emotions. Eight topics were identified through topic modeling: causes and risks, perceptions of China, media and information, infection prevention rules, economic activity, school and infection, political leaders, and religion, politics, and infection. The correlation coefficient between fear and anger was 0.462 (p < .001), indicating a moderate linear relationship between the two emotions. Fear was the highest from January to March in the first year of the COVID-19 outbreak, while anger occurred before and after the outbreak, with fluctuations in both emotions during this period. This study confirmed that social cognitions and negative emotions are intertwined in response to major events related to the COVID-19 pandemic, with each emotion varying individually rather than being ambiguously mixed. These findings could aid in developing social cognition-emotion-based public health strategies through education and communication during future pandemic outbreaks.
Sections du résumé
BACKGROUND
BACKGROUND
The COVID-19 pandemic has been the most widespread and threatening health crisis experienced by the Korean society. Faced with an unprecedented threat to survival, society has been gripped by social fear and anger, questioning the culpability of this pandemic. This study explored the correlation between social cognitions and negative emotions and their changes in response to the severe events stemming from the COVID-19 pandemic in South Korea.
METHODS
METHODS
The analysis was based on a cognitive-emotional model that links fear and anger to the social causes that trigger them and used discursive content from comments posted on YouTube's COVID-19-related videos. A total of 182,915 comments from 1,200 videos were collected between January and December 2020. We performed data analyses and visualizations using R, Netminer 4.0, and Gephi software and calculated Pearson's correlation coefficients between emotions.
RESULTS
RESULTS
YouTube videos were analyzed for keywords indicating cognitive assessments of major events related to COVID-19 and keywords indicating negative emotions. Eight topics were identified through topic modeling: causes and risks, perceptions of China, media and information, infection prevention rules, economic activity, school and infection, political leaders, and religion, politics, and infection. The correlation coefficient between fear and anger was 0.462 (p < .001), indicating a moderate linear relationship between the two emotions. Fear was the highest from January to March in the first year of the COVID-19 outbreak, while anger occurred before and after the outbreak, with fluctuations in both emotions during this period.
CONCLUSIONS
CONCLUSIONS
This study confirmed that social cognitions and negative emotions are intertwined in response to major events related to the COVID-19 pandemic, with each emotion varying individually rather than being ambiguously mixed. These findings could aid in developing social cognition-emotion-based public health strategies through education and communication during future pandemic outbreaks.
Identifiants
pubmed: 38835010
doi: 10.1186/s12889-024-19023-6
pii: 10.1186/s12889-024-19023-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1496Subventions
Organisme : National Research Foundation of Korea
ID : 2020S1A6A3A03063902
Organisme : National Research Foundation of Korea
ID : 2021R1A2C2095271
Informations de copyright
© 2024. The Author(s).
Références
Jeyanathan M, Afkhami S, Fiona S, Miller MS, Lichty BD, Xing Z. Immunological considerations for COVID-19 vaccine strategies. Nat Rev Immunol. 2020;20:615–32. https://doi.org/10.1038/s41577-020-00434-6 .
doi: 10.1038/s41577-020-00434-6
pubmed: 32887954
pmcid: 7472682
Kim E-A. Social distancing and public health guidelines at workplaces in Korea: responses to coronavirus disease-19. Saf Health Work. 2020;11:275–83. https://doi.org/10.1016/j.shaw.2020.07.006 .
doi: 10.1016/j.shaw.2020.07.006
pubmed: 32837740
pmcid: 7371589
Seong H, Hyun HJ, Yun JG, Noh JY, Cheong HJ, Kim WJ, Song JY. Comparison of the second and third waves of the COVID-19 pandemic in South Korea: importance of early public health intervention. Int J Infect Dis. 2021;104:742–5. https://doi.org/10.1016/j.ijid.2021.02.004 .
doi: 10.1016/j.ijid.2021.02.004
pubmed: 33556610
pmcid: 7863747
Mohammed AZ, Alsinglawi B, Omar OM, Fady Alnajjar. Measurement method for evaluating the lockdown policies during the COVID-19 pandemic. Int J Environ Res Public Health. 2020;17:5574–83. https://doi.org/10.3390/ijerph17155574 .
doi: 10.3390/ijerph17155574
Ganesan Balasankar, AdelAl-Jumaily KNK, Fong P, Prasad. Surendra Kumar Meena, Raymond Kai-Yu Tong. Impact of coronavirus disease 2019 (COVID-19) outbreak quarantine, isolation, and lockdown policies on mental health and suicide. Front Psychiatry. 2021;12:565190. https://doi.org/10.3389/fpsyt.2021.565190 .
doi: 10.3389/fpsyt.2021.565190
Kim SW. COVID-19 outbreak in Daegu City, Korea and response to COVID-19: how have we dealt and what are the lessons? J Korean Med Sci. 2022;37(50):e356. https://doi.org/10.3346/jkms.2022.37.e356 .
doi: 10.3346/jkms.2022.37.e356
pubmed: 36573388
pmcid: 9792262
Lee Jong-Koo. Challenging issues caused by COVID-19—A window of opportunity to make our health system healthier. Osong Public Health Res Perspect. 2020;11:267–8. https://doi.org/10.24171/j.phrp.2020.11.5.01 .
doi: 10.24171/j.phrp.2020.11.5.01
pubmed: 33117630
pmcid: 7577387
Lee Jong-Koo. The policy art of the ‘trade-off’ for combatting COVID-19. Osong Public Health Res Perspect. 2020;12:137–8. https://doi.org/10.24171/j.phrp.2021.0150 .
doi: 10.24171/j.phrp.2021.0150
Brouard S, Foucault M, Michel E, Becher M, Vasilopoulos P, Bono P-H, Sormani N. Citizens’ attitudes under COVID19, a cross-country panel survey of public opinion in 11 advanced democracies. Sci Data. 2022;9:108. https://doi.org/10.1038/s41597-022-01249-x .
doi: 10.1038/s41597-022-01249-x
pubmed: 35347140
pmcid: 8960763
Ning L, Niu J, Bi X, Yang C, Liu Z, Wu Q, Ning N, Liang L, Liu A, Hao Y, Gao L. The impacts of knowledge, risk perception, emotion and information on citizens’ protective behaviors during the outbreak of COVID-19: a cross-sectional study in China. BMC Public Health. 2020;20:1751. https://doi.org/10.1186/s12889-020-09892-y .
doi: 10.1186/s12889-020-09892-y
pubmed: 33225934
pmcid: 7681179
Gong J, Firdaus A, Said F, Ali Aksar I, Danaee M, Xu J. Pathways linking media use to wellbeing during the COVID-19 pandemic: a mediated moderation study. Social Media + Soc. 2022;8(1):1–12. https://doi.org/10.1177/20563051221087390 .
doi: 10.1177/20563051221087390
Fingerman KL, Ng YT, Zhang S, Britt K, Colera G, Birditt KS, Charles ST. Living alone during COVID-19: social contact and emotional well-being among older adults. J Gerontol B Psycholl Sci Soc Sci. 2021;76:e116–21. https://doi.org/10.1093/geronb/gbaa200 .
doi: 10.1093/geronb/gbaa200
Pedrosa AL, Bitencourt L, Fróes AC, Cazumbá ML, Campos RG, de Brito SB. Simões E Silva AC. Emotional, behavioral, and psychological impact of the COVID-19 pandemic. Front Psychol. 2020;11:566212. https://doi.org/10.3389/fpsyg.2020.566212 .
doi: 10.3389/fpsyg.2020.566212
pubmed: 33117234
pmcid: 7561666
Bland AR, Roiser JP, Mehta MA, Sahakian BJ, Robbins TW, Elliott R. The impact of COVID-19 social isolation on aspects of emotional and social cognition. Cogn Emot. 2022;36:49–58. https://doi.org/10.1080/02699931.2021.1892593 .
doi: 10.1080/02699931.2021.1892593
pubmed: 33632068
Ying W, Cheng C. Public emotional and coping responses to the COVID-19 Infodemic: a review and recommendations. Front Psychiatry. 2021;12:755938. https://doi.org/10.3389/fpsyt.2021.755938 .
doi: 10.3389/fpsyt.2021.755938
pubmed: 34970164
pmcid: 8712438
Limaye RJ, Sauer M, Ali J, Bernstein J, Wahl B, Barnhill A, Labrique A. Building trust while influencing online COVID-19 content in the social media world. Lancet Digit Health. 2020;2(6):e277–8. https://doi.org/10.1016/S2589-7500(20)30084-4 .
doi: 10.1016/S2589-7500(20)30084-4
pubmed: 32322814
pmcid: 7173823
Roseman IJ, Smith CA. Appraisal theory: overview, assumptions, varieties, controversies. In: Scherer KR, Schorr A, Johnstone T, editors. Appraisal processes in emotion: theory, methods, research. New York: Oxford University Press; 2001. pp. 3–19.
doi: 10.1093/oso/9780195130072.003.0001
Ahn J, Kim HK, Kahlor LA, Atkinson L, Noh GY. The impact of emotion and government trust on individuals’ risk information seeking and avoidance during the COVID-19 pandemic: a cross-country comparison. J Health Commun. 2021;26:728–41. https://doi.org/10.1080/10810730.2021.1999348 .
doi: 10.1080/10810730.2021.1999348
pubmed: 34779340
Han J, Cha M, Lee W. Anger contributes to the spread of COVID-19 misinformation. HKS Misinfo Rev. 2020;1:1–14. https://doi.org/10.37016/mr-2020-39 .
doi: 10.37016/mr-2020-39
Kang M, Kim JR, Cha H. From concerned citizens to activists: a case study of 2015 South Korean MERS outbreak and the role of dialogic government communication and citizens’ emotions on public activism. J Public Relat Res. 2018;30(5–6):202–29. https://doi.org/10.1080/1062726X.2018.1536980 .
doi: 10.1080/1062726X.2018.1536980
Lazarus RS. Relational meaning and discrete emotions. In: Scherer KR, Schorr A, Johnstone T, editors. Appraisal processes in emotion: theory, methods, research. New York: Oxford University Press; 2001.
Parkinson B, Simons G. Affecting others: social appraisal and emotion contagion in everyday decision making. Pers Soc Psychol Bull. 2009;35:1071–84. https://doi.org/10.1177/0146167209336611 .
doi: 10.1177/0146167209336611
pubmed: 19474455
Roseman IJ, Smith CA. Appraisal theory: overview, assumptions, varieties, controversies. In: Scherer KR, Schorr A, Johnstone T, editors. Appraisal processes in emotion: theory, methods, research. New York: Oxford University Press; 2001.
Lerner JS, Keltner D. Fear, anger, and risk. J Pers Soc Psychol. 2001;81:146–59. https://doi.org/10.1037//0022-3514.81.1.146 .
doi: 10.1037//0022-3514.81.1.146
pubmed: 11474720
Ekman P. Emotions revealed: recognizing faces and feelings to improve communication and emotional life. New York: Times Books; 2003.
Lazarus RS. Emotion and adaptation. Oxford: Oxford University Press; 1991.
doi: 10.1093/oso/9780195069945.001.0001
Plutchik R. A general psychoevolutionary theory of emotion. Theories of emotion. Cambridge: Academic; 1980.
Young SD. Recommendations for using online social networking technologies to reduce inaccurate online health information. Online J Health Allied Sci. 2011;10(2).
Li S, Wang Y, Xue J, Zhao N, Zhu T. The impact of COVID-19 epidemic declaration on psychological consequences: a study on active Weibo users. Int J Environ Res Public Health. 2020;17(6):2032. https://doi.org/10.3390/ijerph17062032 .
doi: 10.3390/ijerph17062032
pubmed: 32204411
pmcid: 7143846
Wu YQ, Gong J. Mobile social media as a vehicle of health communication: a multimodal discourse analysis of WeChat official account posts during the COVID-19 crisis. Humanit Soc Sci Commun. 2023;10(1):1–12. https://doi.org/10.1057/s41599-023-02259-9 .
doi: 10.1057/s41599-023-02259-9
Lim E, Shin J, Park S. A textmining study on emotional cognition, understanding, and preventative behaviors during the COVID-19 pandemic. BMC Public Health. 2023;23:282. https://doi.org/10.1186/s12889-023-15180-2 .
doi: 10.1186/s12889-023-15180-2
pubmed: 36864419
pmcid: 9981253
Chen M, Shen F, Yu W, Chu Y. The relationship between government trust and preventive behaviors during the COVID-19 pandemic in China: exploring the roles of knowledge and negative emotion. Prev Med. 2020;141:106288.
doi: 10.1016/j.ypmed.2020.106288
Goyal K, Chauhan P, Chhikara K, Gupta P, Singh MP. Fear of COVID 2019: first suicidal case in India. Asian J Psychiatry. 2020;49. https://doi.org/10.1016/j.ajp.2020.101989 .
Rieder B, Matamoros-Fernández A, Coromina Ò. From ranking algorithms to ‘ranking cultures’ investigating the modulation of visibility in YouTube search results. Convergence. 2018;24(1):50–68.
doi: 10.1177/1354856517736982
Song M, Park H, Shin KS. Attention-based long short-term memory network using sentiment lexicon embedding for aspect-level sentiment analysis in Korean. Inf Process Manag. 2019;56(3):637–53.
doi: 10.1016/j.ipm.2018.12.005
Zhang W, Xu H, Wan W. Weakness finder: find product weakness from Chinese reviews by using aspects based sentiment analysis. Expert Syst Appl. 2012;39(11):10283–91.
doi: 10.1016/j.eswa.2012.02.166
Charmaz K, Henwood K. Grounded theory methods for qualitative psychology. In: Stainton-Rogers W, Willig C, editors. The SAGE handbook of qualitative research in psychology. 2017:238e256.
Mohammad SM, Turney PD. Nrc emotion lexicon. Natl Res Council Can. 2013;2:234.
Choi S, Lee J, Kang MG, Min H, Chang YS, Yoon S. Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks. Methods. 2017;129:50–9.
doi: 10.1016/j.ymeth.2017.07.027
pubmed: 28813689
pmcid: 7129462
Yun W, Kim D, Kim J. Multi-categorical social media sentiment analysis of corporate events. In: Proceedings of the International Conference on Electronic Commerce. 2017.
Kang SJ, Kim S, Park KH, Jung SI, Shin MH, Kweon SS, Park H, Choi SW, Lee E, Ryu SY. Successful control of COVID-19 outbreak through tracing, testing, and isolation: lessons learned from the outbreak control efforts made in a metropolitan city of South Korea. J Infect Public Health. 2021;14:1151–4. https://doi.org/10.1016/j.jiph.2021.07.003 .
doi: 10.1016/j.jiph.2021.07.003
pubmed: 34364306
pmcid: 8276554
Xu J, Sun G, Cao W, Fan W, Pan Z, Yao Z, Li H. Stigma, discrimination, and hate crimes in chinese-speaking world amid COVID-19 pandemic. Asian J Criminol. 2021;16:51–74. https://doi.org/10.1007/s11417-020-09339-8 .
doi: 10.1007/s11417-020-09339-8
pubmed: 33425062
pmcid: 7785331
Shim J, Lee E, Kim E, Choi Y, Kang G, Kim BI. COVID-19 outbreak in a religious village community in Republic of Korea and risk factors for transmission. Osong Public Health Res Perspects. 2023;14:110–8. https://doi.org/10.24171/j.phrp.2023.0002 .
doi: 10.24171/j.phrp.2023.0002
Bitan DT, Grossman-Giron A, Bloch Y, Mayer Y, Shiffman N, Mendlovic S. Fear of COVID-19 scale: psychometric characteristics, reliability and validity in the Israeli population. Psychiatry Res. 2020;289:113100. https://doi.org/10.1016/j.psychres.2020.113100 .
doi: 10.1016/j.psychres.2020.113100
Adu P, Popoola T, Medvedev ON, Collings S, Mbinta J, Aspin C, Simpson CR. Implications for COVID-19 vaccine uptake: a systematic review. J Infect Public Health. 2023;16:441–66. https://doi.org/10.1016/j.jiph.2023.01.020 .
doi: 10.1016/j.jiph.2023.01.020
pubmed: 36738689
pmcid: 9884645
Chen CW, Lee S, Dong MC, Taniguchi M. What factors drive the satisfaction of citizens with governments’ responses to COVID-19? Int J Infect Dis. 2021;102:327–31. https://doi.org/10.1016/j.ijid.2020.10.050 .
doi: 10.1016/j.ijid.2020.10.050
pubmed: 33115678
Alahmari AA, Khan AA, Alamri FA, Almuzaini YS, Habash AK, Jokhdar H. Healthcare policies, precautionary measures and outcomes of mass gathering events in the era of COVID-19 pandemic: Expedited Review. J Infect Public Health. 2023;28.S1876-0341(23)00106-5. https://doi.org/10.1016/j.jiph.2023.03.026 .
Guo Q, Zheng Y, Shi J, Wang J, Li G, Li C, Fromson JA, Xu Y, Liu X, Xu H, Zhang T, Lu Y, Chen X, Hu H, Tang Y, Yang S, Zhou H, Wang X, Wang Z, Yang Z. Immediate psychological distress in quarantined patients with COVID-19 and its association with peripheral inflammation: a mixed-method study. Brain Behav Immun. 2020;88:17–27. https://doi.org/10.1016/j.bbi.2020.05.038 .
doi: 10.1016/j.bbi.2020.05.038
pubmed: 32416290
pmcid: 7235603
Ma YF, Li W, Deng HB, Wang L, Wang Y, Wang PH, Bo HX, Cao J, Wang Y, Zhu LY, Yang Y, Cheung T, Ng CH, Wu X, Xiang YT. Prevalence of depression and its association with quality of life in clinically stable patients with COVID-19. J Affect Disord. 2020;275:145–8. https://doi.org/10.1016/j.jad.2020.06.033 .
doi: 10.1016/j.jad.2020.06.033
pubmed: 32658818
pmcid: 7329672
Pappa S, Ntella V, Giannakas T, Giannakoulis VG, Papoutsi E, Katsaounou P. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: a systematic review and meta-analysis. Brain Behav Immun. 2020;88:901–7. https://doi.org/10.1016/j.bbi.2020.05.026 .
doi: 10.1016/j.bbi.2020.05.026
pubmed: 32437915
pmcid: 7206431
Oaks SC Jr, Shope RE, Lederberg J, editors. Emerging infections: microbial threats to health in the United States. Washington DC: National Academies; 1992.
Guemghar I, Pires de Oliveira Padilha P, Abdel-Baki A, Jutras-Aswad D, Paquette J, Pomey MP. Social robot interventions in mental health care and their outcomes, barriers, and facilitators: scoping review. JMIR Ment Health. 2022;9(4):e36094.
doi: 10.2196/36094
pubmed: 35438639
pmcid: 9066335
Lattie EG, Stiles-Shields C, Graham AK. An overview of and recommendations for more accessible digital mental health services. Nat Rev Psychol. 2022;1(2):87–100.
doi: 10.1038/s44159-021-00003-1
pubmed: 38515434
pmcid: 10956902
Dakanalis A, Wiederhold BK, Riva G. Artificial intelligence: a game-changer for mental health care. Cyberpsychol Behav Soc Netw. 2024;27(2):100–4.
doi: 10.1089/cyber.2023.0723
pubmed: 38358832
Mesquita B, Frijda NH. Cultural variations in emotions: a review. Psychol Bull. 1992;112(2):179–204. https://doi.org/10.1037/0033-2909.112.2.179 .
doi: 10.1037/0033-2909.112.2.179
pubmed: 1454891