Abstract
This paper focusses on the information asymmetry in crisis news after a serious incident in Tianjin, China, in 2015. The incident caused enormous damage and resulted in societal unrest because of the lack of reliable information from the formal media channels. Social media — micro blogs — played a major role in reporting on crisis situations. We divided netizens (i.e., the citizens of the net) into high and low types according to their information-critical level to the crisis news. The data shows information deterioration on the crisis news, related to the netizens’ information-critical level. For the traditional media there is the opportunity to use information quality distortion to make more marginal profits. This is possible only if the citizens’ information stays under a certain quality level. The result is overprovision of low quality news and high quality news driven out of the market, whereupon adverse selection (i.e., a lack of symmetric information) appears. However, by adopting a process view, we found self-correcting mechanism (i.e., dying out of rumors) of the social media communities in China. We provided a agent-base model and simulation to show that the more media exist in the market, the faster speed of the information deterioration, but also the capacity to ‘discuss’ rumors.
Supported by the National Natural Science Foundation of China (71503178), the National Social Science Fund of China (13ASH003) and China Scholarship Council
References
[1] Shi W, Wang H, He S. Sentiment analysis of Chinese microblogging based on sentiment ontology: A case study of ‘7.23 Wenzhou Train Collision’. Connection Science, 2013, 25(4): 161–178.10.1080/09540091.2013.851172Search in Google Scholar
[2] Bondes M, Schucher G. Derailed emotions: The transformation of claims and targets during the Wenzhou online incident. Information, Communication & Society, 2014, 17(1): 45–65.10.1080/1369118X.2013.853819Search in Google Scholar
[3] Cui K, Zheng X, Zeng D D, et al. An empirical study of information diffusion in micro-blogging systems during emergency events. In Web-Age Information Management, Springer Berlin Heidelberg, 2013.10.1007/978-3-642-39527-7_16Search in Google Scholar
[4] Seeger M W, Sellnow T L, Ulmer R R. Communication and organizational crisis. Greenwood Publishing Group, 2003.Search in Google Scholar
[5] Oh O, Agrawal M, Raghav Rao H. Community intelligence and social media services: A rumor theoretic analysis of tweets during social crises. MIS Quarterly, 2013, 37(2): 407–426.10.25300/MISQ/2013/37.2.05Search in Google Scholar
[6] Jong W, Dückers M L A. Self-correcting mechanisms and echo-effects in social media: An analysis of the “gunman in the newsroom” crisis. Computers in Human Behavior, 2016, 59: 334–341.10.1016/j.chb.2016.02.032Search in Google Scholar
[7] Leibold J. Blogging alone: China, the internet, and the democratic illusion? The Journal of Asian Studies, 2011, 70(4): 1023–1041.10.1017/S0021911811001550Search in Google Scholar
[8] Cacciatore M A, Binder A R, Scheufele D A, et al. Public attitudes toward biofuels: Effects of knowledge, political partisanship, and media use. Politics and the Life Sciences, 2012, 31(1): 36–51.10.2990/31_1-2_36Search in Google Scholar PubMed
[9] Muhren W J, Van de Walle B. A call for sensemaking support systems in crisis management. Interactive Collaborative Information Systems, 2010, 281: 425–452.10.1007/978-3-642-11688-9_16Search in Google Scholar
[10] Garrett R K. Troubling consequences of online political rumoring. Human Communication Research, 2011, 37(2): 255–274.10.1111/j.1468-2958.2010.01401.xSearch in Google Scholar
[11] Afassinou K. Analysis of the impact of education rate on the rumor spreading mechanism. Physica A: Statistical Mechanics and Its Applications, 2014, 414(15): 43–52.10.1016/j.physa.2014.07.041Search in Google Scholar
[12] Peters L D. Conceptualising computer-mediated communication technology and its use in organizations. International Journal of Information Management, 2006, 26(2): 142–152.10.1016/j.ijinfomgt.2005.11.002Search in Google Scholar
[13] Mustafaraj E, Metaxas P T. From obscurity to prominence in minutes: Political speech and real-time search. Web Science Conf, Raleigh, NC, USA, 2010.Search in Google Scholar
[14] Coombs W T. Protecting organization reputations during a crisis: The development and application of situational crisis communication theory. Corporate Reputation Review, 2007, 10(3): 163–176.10.1057/palgrave.crr.1550049Search in Google Scholar
[15] Joslyn M R. Framing the Lewinsky affair: Third-person judgments by scandal frame. Political Psychology, 2003, 24(4): 829–844.10.1046/j.1467-9221.2003.00356.xSearch in Google Scholar
[16] Zhao L, Yin J, Song Y. An exploration of rumor combating behavior on social media in the context of social crises. Computer in Human Behavior, 2016, 58: 25–36.10.1016/j.chb.2015.11.054Search in Google Scholar
[17] Treurniet W, Messemaker M, Wolbers J, et al. Shaping the societal impact of emergencies: Striking a balance between Control and Cooperation. International Journal of Emergency Services, 2015, 4(1): 129–151.10.1108/IJES-06-2014-0007Search in Google Scholar
[18] Arif A, Shanahan K, Chou F J, et al. How information snowballs: Exploring the role of exposure in online rumor propagation. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 2016, 35(4): 466–477.10.1145/2818048.2819964Search in Google Scholar
[19] Akerlof G. The market for lemons: Quality uncertainty and the market mechanism. Quarterly Journal of Economics, 1970, 84(3): 488–500.10.2307/1879431Search in Google Scholar
[20] Lee P S, So C Y, Leung L. Social media and umbrella movement: Insurgent public sphere in formation. Chinese Journal of Communication, 2015, 8(4): 356–375.10.1080/17544750.2015.1088874Search in Google Scholar
[21] House C L, Leahy J V. An sS model with adverse selection. Journal of Political Economy, 2004, 112(3): 581–614.10.1086/383104Search in Google Scholar
[22] Kremhelmer S. Fairness, property rights, and the market for media: Essays in behavioral economics and industrial organization. University München, 2004.Search in Google Scholar
[23] Alexander D E. Social media in disaster risk reduction and crisis management. Science and Engineering Ethics, 2014, 20(3): 717–733.10.1007/s11948-013-9502-zSearch in Google Scholar PubMed
[24] Mendoza M, Poblete B, Castillo C. Twitter under crisis: Can we trust what we RT?. In Proceedings of the First Workshop on Social Media Analytics, ACM, 2010: 71–79.10.1145/1964858.1964869Search in Google Scholar
[25] Winfield B H, Peng Z. Market or party controls? Chinese media in transition. International Communication Gazette, 2005, 67(3): 255–270.10.1177/0016549205052228Search in Google Scholar
[26] Guo L. Collaborative efforts: An exploratory study of citizen media in China. Global Media and Communication, 2012, 8(2): 135–155.10.1177/1742766512444341Search in Google Scholar
[27] Noelle-Neumann E. The spiral of silence: A theory of public opinion. Journal of Communication, 1974, 24(2): 43–51.10.1111/j.1460-2466.1974.tb00367.xSearch in Google Scholar
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Articles in the same Issue
- Conceptualizing Mining of Firm’s Web Log Files
- Duopoly Competition Between Chauffeured Car and Taxi: An Analysis of Pricing and Market Segmentation
- Generating Storyline with Societal Risk from Tianya Club
- Mobility Pattern of Taxi Passengers at Intra-Urban Scale: Empirical Study of Three Cities
- The Role of Social Media in Providing Crisis Information in China: A Critical Evaluation of the Tianjin Fire Incident
- Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism
Articles in the same Issue
- Conceptualizing Mining of Firm’s Web Log Files
- Duopoly Competition Between Chauffeured Car and Taxi: An Analysis of Pricing and Market Segmentation
- Generating Storyline with Societal Risk from Tianya Club
- Mobility Pattern of Taxi Passengers at Intra-Urban Scale: Empirical Study of Three Cities
- The Role of Social Media in Providing Crisis Information in China: A Critical Evaluation of the Tianjin Fire Incident
- Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism