To meet the demands of government crisis response in the evolution of network public opinion, an internet users' negative emotion model based on SOAR(State,Operator and Result) model is proposed, where internet users is treated as Agent, behavior transformation process of internet user group in network public opinion is considered as continuous transformation process of state with time in the corresponding public opinion space in this paper. Then, working memory, long-term memory, decision-making process, learning mechanism of Agent are designed, internet user behavior transformation rule repository is constructed, and SOAR Agent model to reveal behavior transformation rules of internet user group is developed ultimately. Moreover, an simulation experiment is designed, typical public opinion events are seleted as samples, group behavior transformation process of Weibo users under the influence of different government emergency measures is conducted, and the SOAR Agent model of internet users' negative emotion is validated. As result of this research, the collective behavior transformation rules of behavior transfer of internet users in the different environments could be analyzed and predicted based on the modelling of internet users' negative emotion, such as different period of internet public opinion, different government crises response strategy.
WU Peng, QIANG Shao-hua, GAO Qing-ning
. Modelling Internet Users' Negative Emotion Based on SOAR Model[J]. Chinese Journal of Management Science, 2018
, 26(3)
: 126
-138
.
DOI: 10.16381/j.cnki.issn1003-207x.2018.03.014
[1] Liu B F, Austin L, Jin Yan. How publics respond to crisis communication strategies:The interplay of information form and source[J]. Public Relations Review, 2011, 37(4):345-353.
[2] McDonald L M, Sparks B, Glendon A I. Stakeholder reactions to company crisis communication and causes[J]. Public Relations Review, 2010, 36(3):263-271.
[3] Choi Y, Lin Y H. Consumer responses to Mattel product recalls posted on online bulletin boards:Exploring two types of emotion[J]. Journal of Public Relations Research, 2009, 21(2):198-207.
[4] Benoit W. Accounts, excuses and apologies:A theory of image repair strategies[M]. Albany:State University of New York Press, 1995.
[5] Hearit K M. The use of counter-attack in apologetic public relations crises:The case of General Motors vs. Dateline NBC[J]. Public Relations Review, 1996, 22(3):233-248.
[6] Coombs W T. Protecting organization reputations during a crisis:The development and application of situational crisis communication theory[J]. Corporate Reputation Review, 2007, 10(3):163-176.
[7] Jin Yan, Liu B F. The blog-mediated crisis communication model:Recommendations for responding to influential external blogs[J]. Journal of Public Relations Research, 2010, 22(4):429-455.
[8] 刘怡静, 袁建华, 汪李峰. 认知引擎中案例学习模块的设计与实现[J]. 现代电子技术, 2011, 34(9):30-34.
[9] Oyewole S A, Farde A M, Haight J M, et al. Evaluation of complex and dynamic safety tasks in human learning using the ACT-R and SOAR skill acquisition theories[J]. Computers in Human Behavior, 2011, 27(5):1984-1995.
[10] Elster J. Social norms and economic theory[J]. The Journal of Economic Perspectives, 1989,3(4):99-117.
[11] Honey C, Herring S C. Beyond microblogging:Conversation and collaboration via Twitter[C]//Proceedings of the 42nd Hawaii International Conference on System Sciences, Big Island, HI, USA, January 5-8, 2009.
[12] Naaman M, Boase J, Lai C H. Is it really about me?:Message content in social awareness streams[C]//Proceedings of the 2010 ACM conference on Computer Supported Cooperative Work,Savannah, Geogia, USA, February 6-10, 2010.
[13] Riemer K, Richter A. Tweet inside:Microblogging in a corporate context[C]//Proceedings of the 23rd Bled eConference eTrust:Implications for the Individual, Erterprises and Society, Bled, Slovenia, June 20-23, 2010.
[14] Papacharissi Z. Without you, I'm nothing:Performances of the self on Twitter[J]. International Journal of Communication, 2012, 6:838-855.
[15] 方付建. 突发事件网络舆情演变研究[D].武汉:华中科技大学, 2011.
[16] 李纲,陈璟浩. 突发公共事件网络舆情研究综述[J]. 图书情报知识, 2014,(2):111-119.
[17] Coombs W T. The protective powers of crisis response strategies:Managing reputational assets during a crisis[J]. Journal of Promotion Management, 2006, 12(3-4):241-260.
[18] Pang N, Ng J. Twittering the Little India Riot:Audience responses, information behavior and the use of emotive cues[J]. Computers in Human Behavior, 2016, 54:607-619.
[19] Cooley S, Jones A. A forgotten tweet:Somalia and social media[J]. Ecquid Novi:African Journalism Studies, 2013, 34(1):68-82.
[20] Liu B F. Effective public relations in racially-charged crises:Not black or white[M]//Coombs WT, Holladay S J. Handbook of crisis communication, Hoboken, VewJersey:Wiley-Blackwell, 2010:335-358.
[21] DiFonzo N. The watercooler effect:A psychologist explores the extraordinary power of rumors[M]. UK:Penguin,2008.
[22] 陈伟, 情感智能体认知行为建模研究[D]. 长沙:国防科学技术大学,2011.
[23] Laird J E, Nielsen E. Coordinated behavior of computer generated forces in tacAir-Soar[C]//Proceedings of the 4th Conference on Computer Generated Forces and Behavior Represatation, 1994.
[24] Puigbo J Y, Pumarola A, Angulo C, et al. Using a cognitive architecture for general purpose service robot control[J]. Connection Science, 2015, 27(2):105-117.
[25] Zhong Shiquan, Zhou Lizhen, Ma Shoufeng, et al. Guidance compliance behaviors of drivers under different information release modes on VMS[J]. Information Sciences, 2014, 289:117-132.