COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers
By: Ian Kim and Thomas W. Valente
References
- Ahlmén-Laiho, U., Suominen, S., Järvi, U. and Tuominen, R. 2014. “Finnish health journalists’ perceptions of collaborating with medical professionals”, International Conference on Well-Being in the Information Society, Springer, Cham, pp. 1–.
- Anger, I. and Kittl, C. 2011. “Measuring influence on Twitter”, Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, pp. 1–4.
- Ansari, A. 2013. “Green’s art: new media aesthetics in pre-and post-election events in Iran”, Proceedings of the 19th International Symposium of Electronic Art edited by K. Cleland, L. Fisher, and R. Harley, ISEA International, the Australian Network for Art & Technology, and the University of Sydney, Sydney.
- Aramburu, M. J., Berlanga, R. and Lanza, I. 2020. Social media multidimensional analysis for intelligent health surveillance. International Journal of Environmental Research and Public Health 17: 2289.
- Broido, A. D. and Clauset, A. 2019. Scale-free networks are rare. Nature Communications 10: 1–10..
- Centers for Disease Control and Prevention. 2014. Crisis and Emergency Risk Communication (CERC) Manual, Centers for Disease Control and Prevention, Atlanta, available at: https://emergency.cdc.gov/cerc/manual/index.asp.
- Cha, M., Haddadi, H., Benevenuto, F. and Gummadi, P. K. 2010. Measuring user influence in Twitter: the million follower fallacy. Icwsm, 10: 30.
- Clauset, A., Newman, M. E. and Moore, C. 2004. Finding community structure in very large networks. Physical Review E 70: 066111, doi: 10.1103/PhysRevE.70.066111.
- Conover, M. D., Ratkiewicz, J., Francisco, M., Gonçalves, B., Menczer, F. and Flammini, A. 2011. Political polarization on twitter. Fifth international AAAI Conference on Weblogs and Social Media.
- Csardi, G. and Nepusz, T. 2006. The igraph software package for complex network research. InterJournal Complex Systems 1695: 1–9.
- De Brún, A. and McAuliffe, E. 2018. Social network analysis as a methodological approach to explore health systems: a case study exploring support among senior managers/executives in a hospital network. International Journal of Environmental Research and Public Health 15: 511.
- Department of Homeland Security 2018. Countering False Information on Social Media in Disasters and Emergencies: Social Media Working Group for Emergency Services and Disaster Management.
- Fortunato, S. and Barthelemy, M. 2007. Resolution limit in community detection. Proceedings of the National Academy of Sciences 104: 36–41, available at: https://doi.org/10.1073/pnas.0605965104.
- Freeman, L. C. 1977. A set of measures of centrality based on betweenness. Sociometry 40: 35–41, available at: https://doi.org/10.2307/3033543.
- Freeman, L. C. 1979. Centrality in social networks: conceptual clarification. Social Networks 1: 215–239.
- Giglou, R. I., d’Haenens, L. and Van Gorp, B. 2020. “Identifying influential users in Twitter networks of the Turkish Diaspora in Belgium, the Netherlands, and Germany”, Handbook of Research on Politics in the Computer Age, IGI Global, pp. 235–263.
- Girvan, M. and Newman, M. E. 2002. Community structure in social and biological networks. Proceedings of the National Academy of Sciences 99: 7821–7826.
- Gleason, B. 2013. #Occupy Wall Street: exploring informal learning about a social movement on Twitter. American Behavioral Scientist 57: 966–982.
- González-Bailón, S. and Wang, N. 2016. Networked discontent: the anatomy of protest campaigns in social media. Social Networks 44: 95–104.
- Gruzd, A., Wellman, B. and Takhteyev, Y. 2011. Imagining Twitter as an imagined community. American Behavioral Scientist 55: 1294–1318.
- Hagberg, A., Swart, P. and S Chult, D. 2008. Exploring Network Structure, dynamics, and Function using NetworkX(No. LA-UR-08-05495; LA-UR-08-5495) Los Alamos National Lab. (LANL), Los Alamos, NM.
- Hamzehei, A., Jiang, S., Koutra, D., Wong, R. and Chen, F. 2017. Topic-based social influence measurement for social networks. Australasian Journal of Information Systems 21: 61.
- Harris, J. K., Duncan, A., Men, V., Shevick, N., Krauss, M. J. and Cavazos-Rehg, P. A. 2018. Peer Reviewed: Messengers and messages for tweets that Used #thinspo and #fitspo Hashtags in 2016. Preventing Chronic Disease 15, e01, doi: 10.5888/pcd15.170309.
- Harris, J. K., Moreland-Russell, S., Choucair, B., Mansour, R., Staub, M. and Simmons, K. 2014. Tweeting for and against public health policy: response to the Chicago Department of Public Health’s electronic cigarette Twitter campaign. Journal of Medical Internet Research 16: e238.
- Hilton, S. and Hunt, K. 2011. UK newspapers’ representations of the 2009–10 outbreak of swine flu: one health scare not over-hyped by the media?. Journal of Epidemiology and Community Health 65: 941–946.
- Himelboim, I., Lariscy, R. W., Tinkham, S. F. and Sweetser, K. D. 2012. Social media and online political communication: the role of interpersonal informational trust and openness. Journal of Broadcasting & Electronic Media 56: 92–115.
- Himelboim, I., Smith, M. A., Rainie, L., Shneiderman, B. and Espina, C. 2017. Classifying Twitter topic-networks using social network analysis. Social Media+ Society 3.
- Hinds, P. and McGrath, C. 2006. Structures that work: social structure, work structure and coordination ease in geographically distributed teams. Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work, pp. 343–352.
- Homeland Security Council (US) 2006. National Strategy for Pandemic Influenza: Implementation Plan. Executive Office of the President.
- Hossain, L. and Kuti, M. 2010. Disaster response preparedness coordination through social networks. Disasters 34: 755–786.
- Kaalia, R. and Rajapakse, J. C. 2019. Refining modules to determine functionally significant clusters in molecular networks. BMC Genomics 20: 901.
- Kaur, M. and Singh, S. 2016. Analyzing negative ties in social networks: a survey. Egyptian Informatics Journal 17: 21–43.
- Kearney, M. W. 2019. rtweet: collecting and analyzing Twitter data. Journal of Open Source Software 4: 1829
- Kemp, S. 2020. Digital 2020: April Global Statshot, available at: https://datareportal.com/reports/digital-2020-april-global-statshot (accessed May 24, 2020).
- Keshvari, M., Yamani, N., Adibi, P. and Shahnazi, H. 2018. Health journalism: health reporting status and challenges. Iranian Journal of Nursing and Midwifery Research 23: 14.
- Kruikemeier, S. 2014. How political candidates use Twitter and the impact on votes. Computers in Human Behavior 34: 131–139.
- Liang, H., Fung, I. C. H., Tse, Z. T. H., Yin, J., Chan, C. H., Pechta, L. E. and Fu, K. W. 2019. How did Ebola information spread on twitter: broadcasting or viral spreading?. BMC Public Health 19: 438.
- Littau, J. and Jahng, M. R. 2016. Interactivity, social presence, and journalistic use of Twitter. # ISOJ Journal 6: 71–90.
- Lossio-Ventura, J. A. and Alatrista-Salas, H. (Eds), 2017. Information Management and Big Data: Second Annual International Symposium, SIMBig 2015, Cusco, Peru, September 2-4, 2015, and Third Annual International Symposium, SIMBig 2016, Cusco, Peru, September 1-3, 2016, Revised Selected Papers (Vol. 656), Springer.
- Majmundar, A., Allem, J. P., Cruz, T. B. and Unger, J. B. 2018. The why we retweet scale. PLoS ONE 13: e0206076, available at: https://doi.org/10.1371/journal.pone.0206076.
- Martin, J. G. III 2012. Visualizing the Invisible: Application of Knowledge Domain Visualization to the Longstanding Problem of Disciplinary and Professional Conceptualization in Emergency and Disaster Management. Universal-Publishers, Charles Town, MA.
- Matsa, K. E. and Shearer, E. 2018. News use across social media platforms 2018. Pew Research Center.
- Moody, J., McFarland, D. and Bender-deMoll, S. 2005. Dynamic network visualization. American Journal of Sociology 110: 1206–1241.
- Morris, M. R., Counts, S., Roseway, A., Hoff, A. and Schwarz, J. 2012. Tweeting is believing? Understanding microblog credibility perceptions. Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, pp. 441–450.
- Recuero, R., Zago, G. and Soares, F. 2019. Using social network analysis and social capital to identify user roles on polarized political conversations on Twitter. Social Media+ Society 5: 205630511984874.
- Shin, J., Jian, L., Driscoll, K. and Bar, F. 2017. Political rumoring on Twitter during the 2012 US presidential election: rumor diffusion and correction. New Media & Society 19: 1214–1235.
- Shin, J., Jian, L., Driscoll, K. and Bar, F. 2018. The diffusion of misinformation on social media: temporal pattern, message, and source. Computers in Human Behavior 83: 278–287.
- Staniland, K. and Smith, G. 2013. Flu frames. Sociology of Health & Illness 35: 309–324.
- Takeichi, Y., Sasahara, K., Suzuki, R. and Arita, T. 2015. Concurrent bursty behavior of social sensors in sporting events. PLoS ONE 10: e0144646.
- Valente, T. W. 1995. Network Models of the Diffusion of Innovations, Hampton Press, Cresskill, NJ.
- Valente, T. W. 2010. Social Networks and Health: Models, Methods, and Applications, Oxford University Press.
- Wang, J., Cellary, W., Wang, D., Wang, H., Chen, S. C., Li, T. and Zhang, Y. (Eds), 2015. Web Information Systems Engineering–WISE 2015: 16th International Conference, Miami, FL, USA, November 1–3, 2015, Proceedings (Vol. 9418), Springer.
- Wojcik, S. and Hughes, A. 2019. Sizing up Twitter users Pew Research Center, Washington, DC.
- World Health Organization. 2009. Pandemic Influenza Preparedness and Response: A WHO Guidance Document, World Health Organization, Geneva.
- Yang, J. and Counts, S. 2010. Predicting the speed, scale, and range of information diffusion in Twitter. 4th International AAAI Conference on Weblogs and Social Media (ICWSM), 10: 355–358.
- Zhou, L., Zhang, D., Yang, C. C. and Wang, Y. 2018. Harnessing social media for health information management. Electronic Commerce Research and Applications 27: 139–151.
DOI: https://doi.org/10.21307/connections-2019.018 | Journal eISSN: 2816-4245 | Journal ISSN: 0226-1766
Language: English
Page range: 129 - 142
Published on: Jan 5, 2021
Published by: International Network for Social Network Analysis (INSNA)
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Related subjects:
© 2021 Ian Kim, Thomas W. Valente, published by International Network for Social Network Analysis (INSNA)
This work is licensed under the Creative Commons Attribution 4.0 License.