The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
Unpacking the black box: How to promote citizen engagement through government social media during the COVID-19 crisis
Open accessAbstract
During times of public crises, governments must act swiftly to communicate crisis information effectively and efficiently to members of the public; failure to do so will inevitably lead citizens to become fearful, uncertain and anxious in the prevailing conditions. This pioneering study systematically investigates how Chinese central government agencies used social media to promote citizen engagement during the COVID-19 crisis. Using data scraped from 'Healthy China', an official Sina Weibo account of the National Health Commission of China, we examine how citizen engagement relates to a series of theoretically relevant factors, including media richness, dialogic loop, content type and emotional valence. Results show that media richness negatively predicts citizen engagement through government social media, but dialogic loop facilitates engagement. Information relating to the latest news about the crisis and the government's handling of the event positively affects citizen engagement through government social media. Importantly, all relationships were contingent upon the emotional valence of each Weibo post.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In a pandemic situation, the way health authorities communicate to the population the available information on risks, treatments, vaccination opportunities, or the need for preventive measures may lead to levels of anxiety that determine success or failure to control the current pandemic (Asmundson and Taylor, 2020, Chen et al., 2020).”
From Health-related factors of psychological distress during the COVID-19 pandemic among non-health workers in Spain (2021) · cites this paper as Chen et al., 2020
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Organizational Information Requirements, Media Richness and Structural Design
Daft, R. L., & Lengel, R. H. (1986) · Management Science · doi:10.1287/mnsc.32.5.554 · Cited by 9,868
Uses and Gratifications Research
Katz, E., Blumler, J. G., & Gurevitch, M. (1973) · Public Opinion Quarterly · doi:10.1086/268109 · Cited by 4,012 · cited 2×
“Personal satisfaction with media will directly determine their subsequent media usage (Katz et al., 1973).”
Hilbe, J. M. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9780511973420 · Cited by 3,352
Message Equivocality, Media Selection, and Manager Performance: Implications for Information Systems
Daft, R. L., Lengel, R. H., & Treviño, L. K. (1987) · MIS Quarterly · doi:10.2307/248682 · Cited by 2,322
Hilbe, J. M. (2007) · Cambridge University Press eBooks · doi:10.1017/cbo9780511811852.007 · Cited by 1,998
Emotion Elicits the Social Sharing of Emotion: Theory and Empirical Review
Rimé, B. (2009) · Emotion Review · doi:10.1177/1754073908097189 · Cited by 1,546 · cited 4×
“Emotion will trigger the social sharing of emotion: individuals will openly talk about the specific environment where the emotional event occurred and their own feelings and emotional response with others, or they will share their own emotions by way of letters, journals and other indirect methods (Rim�e, 2009).”
InfluentialBuilding dialogic relationships through the world wide web
Kent, M. L., & Taylor, M. (1998) · Public Relations Review · doi:10.1016/s0363-8111(99)80143-x · Cited by 1,245
Dialogic Engagement: Clarifying Foundational Concepts
Taylor, M., & Kent, M. L. (2014) · Journal of Public Relations Research · doi:10.1080/1062726x.2014.956106 · Cited by 773
Social Media in Disaster Risk Reduction and Crisis Management
Alexander, D. (2013) · Science and Engineering Ethics · doi:10.1007/s11948-013-9502-z · Cited by 593
Rybalko, S., & Seltzer, T. (2010) · Public Relations Review · doi:10.1016/j.pubrev.2010.08.004 · Cited by 551
Flagged first, then by citations
Research works printed but not linked: 1
- Haro-de-Rosario, 2018, 20, 29
Cited by
Sorted by citations
Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., Gupta, B., Lal, B., Misra, S., Prashant, P., et al. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102211 · Cited by 1,232
COVID-19 and digital inequalities: Reciprocal impacts and mitigation strategies
Beaunoyer, E., Dupéré, S., & Guitton, M. J. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106424 · Cited by 1,114
Puri, N., Coomes, E. A., Haghbayan, H., & Gunaratne, K. (2020) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2020.1780846 · Cited by 1,229
Social Media Use for Health Purposes: Systematic Review
Chen, J., & Wang, Y. (2021) · Journal of Medical Internet Research · doi:10.2196/17917 · Cited by 1,073
What social media told us in the time of COVID-19: A scoping review
Tsao, S.-F., Chen, H., Tisseverasinghe, T., Yang, Y., Li, L., & Butt, Z. A. (2021) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30315-0 · Cited by 816
Dynamic digital capabilities and supply chain resilience: The role of government effectiveness
Dubey, R., Bryde, D., Dwivedi, Y. K., Graham, G., Foropon, C. R. H., & Παπαδόπουλος, Θ. (2023) · International Journal of Production Economics · doi:10.1016/j.ijpe.2023.108790 · Cited by 588
Su, Z., McDonnell, D., Wen, J., Kozak, M., Abbas, J., Šegalo, S., Li, X. A., Aḥmad, J., Cheshmehzangi, A., Cai, Y., et al. (2021) · Globalization and Health · doi:10.1186/s12992-020-00654-4 · Cited by 455
Li, Y., Guan, M., Hammond, P., & Berrey, L. E. (2021) · Health Education Research · doi:10.1093/her/cyab010 · Cited by 337
Assessing behavioral data science privacy issues in government artificial intelligence deployment
Saura, J. R., Soriano, D. R., & Palacios‐Marqués, D. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2022.101679 · Cited by 229
Resilience against crises: COVID-19 and lessons from natural disasters
Sakurai, M., & Chughtai, H. (2020) · European Journal of Information Systems · doi:10.1080/0960085x.2020.1814171 · Cited by 191
Chen, Q., Min, C., Zhang, W., Ma, X., & Evans, R. (2021) · Journal of Medical Internet Research · doi:10.2196/21463 · Cited by 179
Self-citationPérez-Escoda, A., Narros, C. J., de Espinosa, M. P. L., & Esteban, L. M. P. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17145261 · Cited by 177
Covid-19 sentiments in smart cities: The role of technology anxiety before and during the pandemic
Troisi, O., Fenza, G., Grimaldi, M., & Loia, F. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106986 · Cited by 143
Government Digital Transformation: Understanding the Role of Government Social Media
Yuan, Y.-P., Dwivedi, Y. K., Tan, G. W., Cham, T., Ooi, K., Aw, E. C., & Currie, W. L. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2022.101775 · Cited by 191
Tang, Z. R., Miller, A. S., Zhou, Z., & Warkentin, M. E. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101572 · Cited by 137
Zhou, C., Xiu, H., Wang, Y., & Yu, X. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102554 · Cited by 136
Berg, S. H., O'Hara, J. K., Shortt, M. T., Thune, H., Brønnick, K., Lungu, D. A., Røislien, J., & Wiig, S. (2021) · BMC Public Health · doi:10.1186/s12889-021-11468-3 · Cited by 152
Wang, J., Ying, Z., Zhang, W., Evans, R. D., & Zhu, C. (2020) · Journal of Medical Internet Research · doi:10.2196/22152 · Cited by 127
Self-citationAlizadeh, H., Sharifi, A., Damanbagh, S., Nazarnia, H., & Nazarnia, M. (2023) · Natural Hazards · doi:10.1007/s11069-023-05959-2 · Cited by 164
The use of Twitter by state leaders and its impact on the public during the COVID-19 pandemic
Haman, M. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e05540 · Cited by 111
He, Y., Li, W., & Xue, J. (2022) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2022.101223 · Cited by 122
COVID-19, Agriculture, and Food Security in Indonesia
Rozaki, Z. (2020) · Reviews in Agricultural Science · doi:10.7831/ras.8.0_243 · Cited by 108
Zhou, C., Li, K., & Lu, Y. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102679 · Cited by 103
Elavarasan, R. M., Pugazhendhi, R., Shafiullah, G., Irfan, M. F., & Anvari‐Moghaddam, A. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.102789 · Cited by 101
Hruschak, V., Flowers, K. M., Azizoddin, D. R., Jamison, R. N., Edwards, R. R., & Schreiber, K. L. (2020) · Pain · doi:10.1097/j.pain.0000000000002128 · Cited by 104
Food security challenges and opportunities in indonesia post COVID-19
Rozaki, Z. (2021) · Advances in food security and sustainability · doi:10.1016/bs.af2s.2021.07.002 · Cited by 99
Effect of the COVID-19 pandemic on public managers’ attitudes toward digital transformation
Barrutia, J. M., & Echebarria, C. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101776 · Cited by 95
Naeem, M., & Ozuem, W. (2022) · Information Technology & People · doi:10.1108/itp-01-2021-0061 · Cited by 94
Wang, X., Fan, C., Yu, G., & Zhang, K. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107174 · Cited by 97
Li, K., Zhou, C., Luo, X. R., Benitez, J., & Liao, Q. (2022) · Decision Support Systems · doi:10.1016/j.dss.2022.113752 · Cited by 93
Kostkova, P., Saigí-Rubió, F., Eguia, H. A., Borbolla, D. A., Verschuuren, M., Hamilton, C., Muscat, N. A., & Novillo-Ortiz, D. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.707902 · Cited by 83
Mohammed, A., & Ferraris, A. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101651 · Cited by 78
Ruiz-Frutos, C., Ortega-Moreno, M., Allande-Cussó, R., Domínguez-Salas, S., Dias, A., & Gómez-Salgado, J. (2021) · Safety Science · doi:10.1016/j.ssci.2020.104996 · Cited by 76
Research on opinion polarization by big data analytics capabilities in online social networks
Xing, Y., Wang, X., Qiu, C., Li, Y., & He, W. (2022) · Technology in Society · doi:10.1016/j.techsoc.2022.101902 · Cited by 82
Customers' social interactions and panic buying behavior: Insights from social media practices
Naeem, M., & Ozuem, W. (2021) · Journal of Consumer Behaviour · doi:10.1002/cb.1925 · Cited by 77
Social media mining under the COVID-19 context: Progress, challenges, and opportunities
Huang, X., Wang, S., Zhang, M., Hu, T., Hohl, A., She, B., Gong, X., Li, J., Liu, X., Gruebner, O., et al. (2022) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2022.102967 · Cited by 87
Ngai, C. S. B., Singh, R. G., & Yao, L. (2022) · Journal of Medical Internet Research · doi:10.2196/37806 · Cited by 84
Mapping the themes and intellectual structure of customer engagement: a bibliometric analysis
Srivastava, M., & Sivaramakrishnan, S. (2021) · Marketing Intelligence & Planning · doi:10.1108/mip-11-2020-0483 · Cited by 57
Local governments' use of social media during the COVID-19 pandemic: The case of Portugal
Padeiro, M., Bueno-Larraz, B., & Freitas, Â. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101620 · Cited by 78
Superio, D. L., Anderson, K. L., Oducado, R. M. F., Luceño, M. T., Palcullo, V. E. V., & Bendalian, M. V. T. (2021) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2021.102414 · Cited by 73
Characterizing public emotions and sentiments in COVID-19 environment: A case study of India
Das, S., & Dutta, A. K. (2020) · Journal of Human Behavior in the Social Environment · doi:10.1080/10911359.2020.1781015 · Cited by 69
Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence
Adikari, A., Nawaratne, R., Silva, D. D., Ranasinghe, S., Alahakoon, O., & Alahakoon, D. (2021) · Journal of Medical Internet Research · doi:10.2196/27341 · Cited by 70
Behl, A., Dutta, P., Sheorey, P. A., & Singh, R. K. (2020) · The TQM Journal · doi:10.1108/tqm-06-2020-0139 · Cited by 69
Social Media News Use and COVID-19 Misinformation Engagement: Survey Study
Ahmed, S., & Rasul, M. E. (2022) · Journal of Medical Internet Research · doi:10.2196/38944 · Cited by 86
Multilingual topic modeling for tracking COVID-19 trends based on Facebook data analysis
Amara, A., Taieb, M. A. H., & Aouicha, M. B. (2021) · Applied Intelligence · doi:10.1007/s10489-020-02033-3 · Cited by 70
Cyberbullying perpetration in the COVID-19 era: An application of general strain theory
Barlett, C. P., Rinker, A. M., & Roth, B. R. (2021) · The Journal of Social Psychology · doi:10.1080/00224545.2021.1883503 · Cited by 65
Dawi, N. M., Namazi, H., Hwang, H. J., Ismail, S., Marešová, P., & Krejcar, O. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.609716 · Cited by 79
SoleimanvandiAzar, N., Irandoost, S. F., Ahmadi, S., Xosravi, T., Ranjbar, H., Mansourian, M., & Lebni, J. Y. (2021) · BMC Public Health · doi:10.1186/s12889-021-10889-4 · Cited by 67
Landi, S., Costantini, A., Fasan, M., & Bonazzi, M. (2021) · Accounting Auditing & Accountability Journal · doi:10.1108/aaaj-08-2020-4884 · Cited by 63
Alshaabi, T., Arnold, M., Minot, J. R., Adams, J. L., Dewhurst, D. R., Reagan, A. J., Muhamad, R., Danforth, C. M., & Dodds, P. S. (2021) · PLoS ONE · doi:10.1371/journal.pone.0244476 · Cited by 69
Dwivedi, Y. K., Shareef, M. A., Akram, M. S., Bhatti, Z. A., & Rana, N. P. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121364 · Cited by 60
Ruíz-Frutos, C., Ortega‐Moreno, M., Allande‐Cussó, R., Ayuso-Murillo, D., Domínguez‐Salas, S., & Gómez-Salgado, J. C. (2020) · Safety Science · doi:10.1016/j.ssci.2020.105033 · Cited by 59
Cao, J., Liu, F., Shang, M., & Zhou, X. (2021) · Technology and Society · doi:10.1016/j.techsoc.2021.101669 · Cited by 56
Influence of emojis on user engagement in brand-related user generated content
Ko, E. (., Kim, D. W., & Kim, G. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107387 · Cited by 59
Engagement of Government Social Media on Facebook during the COVID-19 Pandemic in Macao
Pang, P. C., Cai, Q., Jiang, W., & Chan, K. S. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18073508 · Cited by 57
The role of social influencers for effective public health communication
Gupta, S., Dash, S. B., & Mahajan, R. (2021) · Online Information Review · doi:10.1108/oir-01-2021-0012 · Cited by 57
Yang, Y., Deng, W., Zhang, Y., & Mao, Z. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18010118 · Cited by 58
Causal Modeling of Twitter Activity during COVID-19
Gencoglu, O., & Gruber, M. (2020) · Computation · doi:10.3390/computation8040085 · Cited by 57
Nunes, N., Björner, E., & Hilding-Hamann, K. E. (2021) · Sustainability · doi:10.3390/su132313378 · Cited by 54
Luo, H., Meng, X., Zhao, Y., & Cai, M. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107733 · Cited by 55
Ju, Y., & Jang, S. S. (2022) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2022.103357 · Cited by 52
Cadel, L., Marcinow, M. L., Sandercock, J., Dowedoff, P., Guilcher, S. J. T., Maybee, A., Law, S., & Kuluski, K. (2021) · PLoS ONE · doi:10.1371/journal.pone.0257880 · Cited by 50
Cheng, Y., Wang, Y., & Kong, Y. (2022) · Public Relations Review · doi:10.1016/j.pubrev.2022.102172 · Cited by 49
Jiang, H., & Tang, X. (2022) · Public Administration · doi:10.1111/padm.12845 · Cited by 52
Villodre, J., & Criado, J. I. (2020) · Government Information Quarterly · doi:10.1016/j.giq.2020.101521 · Cited by 47
Wang, X., & Lee, E. W. J. (2020) · Internet Research · doi:10.1108/intr-04-2020-0181 · Cited by 47
Zhong, W., Hu, Q., & Kapucu, N. (2022) · Public Administration · doi:10.1111/padm.12855 · Cited by 51
Lerouge, R., Lema, M. D., & Arnaboldi, M. (2023) · Government Information Quarterly · doi:10.1016/j.giq.2022.101798 · Cited by 46
Dong, C., Zheng, Q., & Morehouse, J. (2023) · Public Relations Review · doi:10.1016/j.pubrev.2022.102284 · Cited by 46
Al-Omoush, K. S., Yserte, R. G., & Cañero, J. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113748 · Cited by 67
Understanding the effects of message cues on COVID ‐19 information sharing on Twitter
Zheng, H., Goh, D. H., Lee, E. W. J., Lee, C. S., & Theng, Y. (2021) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24587 · Cited by 46
Selerio, E., Caladcad, J. A., Catamco, M. R., Capinpin, E. M. A., & Ocampo, L. A. (2021) · Socio-Economic Planning Sciences · doi:10.1016/j.seps.2021.101217 · Cited by 48
Getting through COVID-19 together: Understanding local governments' social media communication
Górska, A. M., Dobija, D., Grossi, G., & Staniszewska, Z. (2021) · Cities · doi:10.1016/j.cities.2021.103453 · Cited by 45
Alhassan, F. M., & AlDossary, S. A. (2021) · JMIR Public Health and Surveillance · doi:10.2196/27942 · Cited by 45
Cho, W., & Melisa, W. D. (2021) · Administrative Sciences · doi:10.3390/admsci11020059 · Cited by 51
Ufua, D. E., Osabuohien, E. S. C., Ogbari, M. E., Falola, H. O., Okoh, E. E., & Lakhani, A. (2021) · Global Journal of Flexible Systems Management · doi:10.1007/s40171-021-00263-z · Cited by 44
Tam, L. T., Ho, H. X., Nguyen, D. P., Elias, A. A., & Le, A. N. H. (2021) · Global Journal of Flexible Systems Management · doi:10.1007/s40171-021-00269-7 · Cited by 44
He, C., Liu, H., He, L., Lu, T., & Li, B. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107019 · Cited by 44
Influence of information attributes on information dissemination in public health emergencies
Cai, M., Luo, H., Meng, X., Cui, Y., & Wang, W. (2022) · Humanities and Social Sciences Communications · doi:10.1057/s41599-022-01278-2 · Cited by 47
Viralizar la verdad. Factores predictivos del engagement en el contenido verificado en TikTok
García-Marín, D., & Martinrey, G. S. (2022) · El Profesional de la Informacion · doi:10.3145/epi.2022.mar.10 · Cited by 43
Tsoy, D., Godinić, D., Tong, Q., Obrenovic, B., Khudaykulov, A., & Kurpayanidi, K. I. (2022) · Sustainability · doi:10.3390/su14127192 · Cited by 52
Shah, Z., & Wei, L. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.882705 · Cited by 63
Xu, Q., Shen, Z., Shah, N. A., Cuomo, R. E., Cai, M., Brown, M., Li, J., & Mackey, T. K. (2020) · JMIR Public Health and Surveillance · doi:10.2196/24125 · Cited by 41
Jiang, T., Wang, Y., Lin, T., & Shangguan, L. (2020) · Government Information Quarterly · doi:10.1016/j.giq.2020.101548 · Cited by 41
Wu, K., Wu, J., Ding, W., & Tang, R. (2021) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2021.102304 · Cited by 42
Public Opinion Spread and Guidance Strategy under COVID-19: A SIS Model Analysis
Ge, Y., Gan, S., Guo, H., & Dagestani, A. A. (2022) · Axioms · doi:10.3390/axioms11060296 · Cited by 41
Zhang, W., Yuan, H., Zhu, C., Chen, Q., & Evans, R. D. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.807459 · Cited by 40
Self-citationMoss, S. M., & Sandbakken, E. M. (2021) · Political Psychology · doi:10.1111/pops.12727 · Cited by 40
Huang, Q., Jin, J., Lynn, B. J., & Men, L. R. (2021) · Public Relations Review · doi:10.1016/j.pubrev.2021.102064 · Cited by 43
Pup-ularity contest: The advertising practices of popular animal influencers on Instagram
Jacobson, J., Hodson, J., & Mittelman, R. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121226 · Cited by 50
Building digital resilience against crises: The case of Taiwan's COVID ‐19 pandemic management
Lee, J. Y., Chou, C., Chang, H., & Hsu, C. W. (2023) · Information Systems Journal · doi:10.1111/isj.12471 · Cited by 51
Social media engagement forms in government: A structure-content framework
Wukich, C. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2022.101684 · Cited by 52
Mapping the knowledge frontiers of public risk communication in disaster risk management
Agyepong, L. A., & Liang, X. (2022) · Journal of Risk Research · doi:10.1080/13669877.2022.2127851 · Cited by 43
The effects of social media posts’ characteristics on customer engagement: Evidence from WeChat
Xu, Y., Chen, W., & Ow, T. T. (2023) · Information & Management · doi:10.1016/j.im.2023.103854 · Cited by 40
Ahmed, S., & Rasul, M. E. (2023) · Scientific Reports · doi:10.1038/s41598-023-42614-z · Cited by 45
Alamsyah, N., & Zhu, Y. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101646 · Cited by 38
Supervised machine learning models for depression sentiment analysis
Obagbuwa, I. C., Danster, S., & Chibaya, O. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1230649 · Cited by 35
Keren, F., Siddiquei, A. N., Anwar, M., Asmi, F., & Ye, Q. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.664399 · Cited by 35
Koch, J., Plattfaut, R., & Kregel, I. (2021) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2021.100014 · Cited by 36
Paul, S., & Das, S. (2022) · Online Information Review · doi:10.1108/oir-06-2021-0307 · Cited by 34
Metadata
- Authors
- Chen, Q., Min, C., Zhang, W., Wang, G., Ma, X., & Evans, R.
- Affiliations
- Xi'an Jiaotong University (CN)
- City University of Hong Kong (HK)
- Huazhong University of Science and Technology (CN)
- Central China Normal University (CN)
- Brunel University of London (GB)
- Corresponding author
- Zhang, Wei
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 110
- Pages
- 106380
- ISSN
- 0747-5632 (ISSN-L)
- PMC
- PMC7151317
- OpenAlex
- W3015216621
- Cited by
- 652
- References
- 72
- Citations by year
- 2026: 33 · 2025: 64 · 2024: 90 · 2023: 120 · 2022: 133 · 2021: 164 · 2020: 48
- FWCI
- 139.48
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Computers in Human Behavior (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Brunel University Research Archive (BURA) (Brunel University London) (submittedVersion)
- Funders
- National Social Science Foundation of China (17CXW026)
- Topics
- Social Sciences › Communication › Public Relations and Crisis Communication
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Keywords
- citizen participation, government social media, COVID-19 pandemic, crisis communication, Weibo, media richness, content types, emotional valence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
