[目的/意义]探究影响突发公共卫生事件网络虚假信息传播行为的因素，为有针对性地监测预警、阻断传播突发公共卫生事件网络虚假信息提供借鉴参考。[方法/过程]基于S-O-R理论模型，综合考虑外部刺激因素和个体认知因素对传播者信任感知及传播行为的影响，提出相关研究假设，并利用新冠肺疫情期间微博平台的虚假信息进行验证。[结果/结论]突发公共卫生事件的虚假信息质量、信息发布者影响力和事件进展对信息接收者的信息传播行为具有显著促进作用，医护人员主题、呈现积极情感的网络虚假信息更容易获得信任和传播，网络影响力高的信息接收者在虚假信息传播过程中起到辟谣作用。
[Purpose/Significance] This paper aims to explore the influencing factors of network misinformation transmission behaviors in public health emergencies, and to provide references for targeted monitoring, early warning and blocking the spread of network misinformation of public health emergencies. [Method/Process] Based on S-O-R model, this paper considered the influence of external stimulus factors and individual cognitive factors on trust perception and communication behaviors of communicators. On this basis, relevant research hypotheses were put forward and verified by Weibo misinformation data during the COVID-19. [Result/Conclusion] It is found that quality, publishers' influence and event development of misinformation of public health emergencies have significant positive influence on information transmission behaviors of information receivers, network misinformation related to healthcare workers and positive emotion is easier to obtain trust and transmission, and the information receivers with high network influence play a role in refuting rumors in the process of misinformation transmission.
[1] 国家图书馆研究院.中国互联网络信息中心发布第46次《中国互联网络发展状况统计报告》[J].国家图书馆学刊,2020,29(6):19.
[2] 刘诗洋,王倩, 郑秋莹. 我国突发公共卫生事件网络舆情研究现状分析[J]. 管理观察, 2014(10):98-101.
[3] 孙会敏,张菊兰.舆情信息的传播现状分析——以5W模式为视角[J].视听,2019(4):169-170.
[4] 龚鑫. 微博中谣言传播推动者差异性和传播影响研究[D].哈尔滨:哈尔滨工业大学,2020.
[5] ZHAO J, CAO N, WEN Z, et al. F1uxflow:visual analysis of anomalous information spreading on social media[J]. IEEE transactions on visualization and computer graphics, 2014, 20(12):1773-1782.
[6] 易杰. 疫情类网络谣言的传播及治理研究[D].武汉:中南财经政法大学,2017.
[7] 姚艾昕,马捷,林英,等. 重大突发公共卫生事件谣言演化与治理策略研究[J]. 情报科学, 2020, 38(7):22-29.
[8] 陈雅赛. 突发公共卫生事件网络谣言传播与治理研究——基于新冠疫情的网络谣言文本分析[J]. 电子政务, 2020(6):1-11.
[9] MENG D, WAN L, ZHANG L. A study of rumor spreading with epidemic model based on network topology[C]//PENG W. Trends and applications in knowledge discovery and data mining. Berlin:Springer, 2014:381-392.
[10] HALPERN D, VALENZUELA S, KATZ J, et al. From belief in conspiracy theories to trust in others:which factors influence exposure, believing and sharing fake news[C]//MEISELWITZ G. Social computing and social media. design, human behavior and analytics. Berlin:Springer,2019:217-232.
[11] 宋小康,赵宇翔,宋士杰,等.基于MOA理论的健康谣言分享意愿影响因素研究[J].情报学报,2020,39(5):511-520.
[12] 刘晓丹. 社会危机事件中微博谣言传播的影响因素研究[D].大连:大连理工大学,2015.
[13] 栾碧雅. 社交网络虚假信息传播影响因素及治理策略研究[D].长春:吉林大学,2020.
[14] 张迪. 基于用户感知的社交媒体信息可信度研究[D].长春:吉林大学, 2020.
[15] 周高琴.突发事件中恐慌性谣言网络传播的影响因素及治理启示——基于2015-2019年间15起典型案例的扎根研究[J].电子政务,2021(8):94-104.
[16] BODAGHI A, GOLIAEI S, SALEHI M. The number of followings as an influential factor in rumor spreading[J]. Applied mathematics and computation, 2019,357(15):167-184.
[17] TAKENAKA I. Factors influencing rumor transmission:approach from a rating of attributes and purposes of the rumor[J]. Bulletin of mukogawa womens university humanities & social science, 2013, 61:43-52.
[18] 邓胜利, 付少雄. 社交媒体附加信息对用户信任与分享健康类谣言的影响分析[J]. 情报科学, 2018, 36(3):51-57.
[19] JEWCZYN N. Behavioral psychology and educational counseling:an overview of selected origins, current research and the application implications for the academic and career counseling of college students[M]. Bloomington:iUniverse, 2009.
[20] JACOBY J. Stimulus-Organism-Response reconsidered:an evolutionary step in modeling (consumer) behavior[J]. Journal of consumer psychology, 2002, 12(1):51-57.
[21] 赵文德,付荣华,刘世明.社交电商平台的消费者参与意愿影响因素研究——基于S-O-R和UTAUT2模型分析[J].电子商务,2020(8):29-31.
[22] 刘熠. 微博舆情信息受众的参与行为拟合与靶向引导研究[D].长春:吉林大学,2020.
[23] 赖胜强. 网络谣言对受众再传播行为的影响机理研究[J]. 情报杂志, 2014, 33(5):153-156.
[24] 马向阳,徐富明,吴修良,等.说服效应的理论模型、影响因素与应对策略[J].心理科学进展,2012,20(5):735-744.
[25] 张婷,齐向华.知乎信息起源模型及可信度评估[J].图书情报工作,2019,63(9):85-94.
[26] LEWANDOWSKY S, ECKER U K H, SEIFERT C M, et al. Misinformation and its correction continued influence and successful debiasing[J]. Psychological science in the public interest, 2012,13(3):106-131.
[27] 熊炎.何种谣言更具传播力?——谣言内容、传谣意愿与谣言讨论热度[J].现代传播(中国传媒大学学报),2016,38(9):71-75.
[28] BERGER J, MILKMAN K L. What makes online content viral?[J]. Journal of marketing research, 2012,49(2):192-205.
[29] 张志安,束开荣,何凌南. 微信谣言的主题与特征[J].新闻与写作, 2016(1):60-64.
[30] BERGER J. Word of mouth and interpersonal communication:a review and directions for future research[J]. Journal of consumer psychology, 2014, 24(4):586-607.
[31] 翟羽佳,过南杉,阎嘉琪.突发公共卫生事件中虚假信息的时滞性扩散与情感关联分析[J].情报科学,2021,39(5):62-69.
[32] 卡普费雷. 谣言:世界最古老的传媒[M]. 郑若麟,译.上海:上海人民出版社, 2008.
[33] 张帅,刘运梅,司湘云.信息疫情下网络虚假信息的传播特征及演化规律[J].情报理论与实践,2021,44(8):112-118.
[34] 赵领帅. 微博用户转发预测特征的特征选择研究[D].西安:西北大学,2018.
[35] 北京日报. 微博Q1财报:疫情期间月活用户增8500万[EB/OL].[2021-07-11]. https://baijiahao.baidu.com/s?id=1667121175747599904&wfr=spider&for=pc.
[36] 祖坤琳, 赵铭伟, 郭凯,等. 新浪微博谣言检测研究[J]. 中文信息学报, 2017, 31(3):198-204.
[37] 曾艳. 基于集成学习的微博谣言识别与危害性评估[D].重庆:重庆邮电大学,2020.
[38] 白静.抗疫斗争充分彰显中国治理能力和科技创新支撑——《抗击新冠肺炎疫情的中国行动》白皮书发布[J].中国科技产业,2020(6):35-36.
[39] 谢海华,李培维. 重大疫情中的谣言传播与协同辟谣研究[J]. 今传媒, 2020, 28(10):139-143.
[40] 彭晓哲, 崔芳, 焦璨,等. 谣言传播的情境、内容、传播者与受众特征及相关认知神经科学研究[J]. 心理科学, 2018, 41(4):916-921.
[41] 王灿发, 于印珠. 新冠肺炎疫情中谣言传播的阶段性特征及辟谣策略探析[J]. 中国报业, 2020, 488(7):18-21.
