Research on the Evolution Trend of Group Psychological Security Risks Under Public Health Emergencies: Mining and Analysis Based on Social Media Data

References

• Wang J, Long R, Chen H, Li Q. Measuring the psychological security of urban residents: construction and validation of a new scale. Front Psychol. 2019;10:2423. doi:10.3389/fpsyg.2019.02423
   PubMed Web of Science ®Google Scholar
• Hua XM. Research on the Relationship of Psychological Security and Insecurity of University Students. Beijing: China University of Geosciences; 2013.
   Google Scholar
• Beaudoin CE, Hong T. Emotions in the time of coronavirus: antecedents of digital and social media use among Millennials. Comput Human Behav. 2021;123:106876. doi:10.1016/j.chb.2021.106876
   PubMed Web of Science ®Google Scholar
• Bian XH, Xu T. Evolution of public sentiments during COVID-19 pandemic. Data Anal Knowl Discov. 2022;6(7):128–140.
   Google Scholar
• Li W, Chen J, Ma H, Feng X. Research on emotional polarization mechanism of knowledge community from the perspective of social network structure—an empirical study on ‘Zhihu’ question and answer learning community. Front Phys. 2023;11:1139475. doi:10.3389/fphy.2023.1139475
   Web of Science ®Google Scholar
• Yang J, Liu X, Li Z, Zhou H. Group counterattack to destination infringement events: media empowerment and emotional conduction regarding interactive ritual theory. Curr Issues Tour. 2023. doi:10.1080/13683500.2023.2224551
   Web of Science ®Google Scholar
• Yu X, Nian F, Yao Y, Luo L. Phase transition in group emotion. IEEE Trans Comput Soc Syst. 2021;8(5):1143–1152. doi:10.1109/TCSS.2021.3073899
   Web of Science ®Google Scholar
• van Haeringen ES, Gerritsen C, Hindriks KV. Emotion contagion in agent-based simulations of crowds: a systematic review. Auton Agent Multi Agent Syst. 2023;37(1):1–41. doi:10.1007/s10458-022-09589-z
   Web of Science ®Google Scholar
• Wu WD. Risk of social psychology in megacity: features, mechanism and intervention. Shanghai Urban Manag. 2021;30(6):44–51.
   Google Scholar
• Veltmeijer EA, Gerritsen C, Hindriks KV. Automatic emotion recognition for groups: a review. IEEE Trans Affect Comput. 2023;14(1):89–107.
   Web of Science ®Google Scholar
• Wang X, Zhang D, Tan HZ, Lee DJ. A self-fusion network based on contrastive learning for group emotion recognition. IEEE Trans Comput Soc Syst. 2023;10(2):458–469. doi:10.1109/TCSS.2022.3202249
   Web of Science ®Google Scholar
• Yao CY, Wang D, Yang YH, Fu DP. Research on the dynamics model of group emotions evolution based on topic resonance. Syst Eng Theory Pract. 2022;42(9):2523–2539.
   Google Scholar
• Sharma G, Dhall A, Cai J. Audio-visual automatic group affect analysis. IEEE Trans Affect Comput. 2023;14(2):1056–1069. doi:10.1109/TAFFC.2021.3104170
   Web of Science ®Google Scholar
• Liu F. Research on the Spread of Psychological Security/Psychological Insecurity in Group Based on the Theory of Emotional Contagion. Beijing;: China University of Geosciences; 2016.
   Google Scholar
• Zhang D. Does the subsistence allowance system improve the sense of subjective well-being, acquisition and security of the poor? An empirical analysis based on CFPS panel data. Commer Res. 2020; 7:136–144.
   Google Scholar
• Chae SW, Lee SH. Sharing emotion while spectating video game play: exploring Twitch users’ emotional change after the outbreak of the COVID-19 pandemic. Comput Human Behav. 2022;131:107211. doi:10.1016/j.chb.2022.107211
   PubMed Web of Science ®Google Scholar
• Zhu XX, Song JX, Meng JF. Analysis of online public opinion information based on the dynamic theme-emotion evolution model. Inf Sci. 2019;37(7):72–78.
   Google Scholar
• Feng X, Wang X, Zhang Y. Research on public emotional polarization and public opinion evolution of OTC and learning during the COVID-19 epidemic: taking the topic of OTC on Zhihu as an example. Libr Hi Tech. 2022;40(2):286–303. doi:10.1108/LHT-09-2021-0323
   Web of Science ®Google Scholar
• Adikari A, Gamage G, de Silva D, Mills N, Wong SMJ, Alahakoon D. A self structuring artificial intelligence framework for deep emotions modeling and analysis on the social web. Futur Gener Comput Syst. 2021;116:302–315. doi:10.1016/j.future.2020.10.028
   Web of Science ®Google Scholar
• Liu B, Li MF, Xiao GF, Huo L. An empirical study on risk prediction and decision-making model of major public health emergencies: a case study of COVID-19 prevention and control war in Wuhan. Inf Sci. 2022;40(8):118–126.
   Google Scholar
• Fink S. Crisis Management: Planning for the Inevitable. California: Amacom; 1986.
   Google Scholar
• Xu LH, Lin HF, Pan Y, Ren H, Chen JM. Constructing the affective lexicon ontology. J China Soc Sci Tech Inf. 2008;27(2):180–185.
   Google Scholar
• Gao Y, Liu H. How to enhance psychological security of enterprise employees during the COVID-19 pandemic: based on MRA and fsQCA. Curr Psychol. 2022. doi:10.1007/s12144-022-03775-8
   Web of Science ®Google Scholar
• Zou S. Relationship of Social Security Events and Psychological Security, Subjective Well-Being. Beijing: China University of Geosciences; 2012.
   Google Scholar
• Li X, Zeng X. Expected income of new currency in blockchain based on data-mining technology. Electron. 2020;9(1):160. doi:10.3390/electronics9010160
   Web of Science ®Google Scholar
• Mi C, Li M, Wulandari AF. Predicting video views of web series based on comment sentiment analysis and improved stacking ensemble model. Electron Commer Res. 2022. doi:10.1007/s10660-022-09642-9
   Web of Science ®Google Scholar
• Guo XH, Zhang YQ, Yang KX. Fine-grained sentiment analysis based on Weibo. Data Anal Knowl Discov. 2017;1(7):61–72.
   Google Scholar
• Han ZM, Zhang YS, Zhang H, Wan YL, Huang JH. On effective short text tendency classification algorithm for Chinese microblogging. Comput Appl Softw. 2012;29(10):89–93+82.
   Google Scholar
• Han J, Feng Y, Li N, et al. Correlation between word frequency and 17 items of Hamilton scale in major depressive disorder. Front Psychiatry. 2022;13:902873. doi:10.3389/fpsyt.2022.902873
   PubMed Web of Science ®Google Scholar
• Adikari A, Alahakoon D. Understanding citizens’ emotional pulse in a smart city using artificial intelligence. IEEE Trans Ind Informatics. 2021;17(4):2743–2751. doi:10.1109/TII.2020.3009277
   Web of Science ®Google Scholar
• Kaur J, Parmar KS, Singh S. Autoregressive models in environmental forecasting time series: a theoretical and application review. Environ Sci Pollut Res. 2023;30(8):19617–19641. doi:10.1007/s11356-023-25148-9
   PubMed Web of Science ®Google Scholar
• Kelley TL. The selection of upper and lower groups for the validation of test items. J Educ Psychol. 1939;30:17–24. doi:10.1037/h0057123
   Google Scholar