针对社交媒体平台中健康谣言广泛传播的现象,通过添加警告为减少在线健康谣言的传播提供干预建议。基于信息级联理论和消极偏见理论等,采用网络情景实验,在SPSS 26.0软件中进行数据分析,探究当谣言类型分别为恐惧谣言和希望谣言时,不同形式的警告对用户分享意愿的影响。研究结果表明,在健康谣言下方添加警告可以降低用户对其分享的意愿;相较于一般用户警告,好友警告和专家警告对健康谣言分享意愿的减少更明显;相较于好友警告,专家警告更能减少健康谣言分享意愿;与希望谣言相比,三种形式的警告都对恐惧谣言分享意愿的减少更明显。
In view of the widespread spread of health rumors on social media platforms, add warnings to pro-vide intervention suggestions to reduce the spread of online health rumors. Based on the infor-mation cascade theory and the negative bias theory, data analysis was performed in the SPSS 26.0 software, this paper uses the network scenario experiment to explore the impact of different forms of warnings on users’ willingness to share when the types of rumors are fear rumors and hope ru-mors respectively. The results show that adding warnings under health rumors can reduce users’ willingness to share. Compared with general user warnings, friend warnings and expert warnings reduce the willingness to share health rumors more significantly. Expert warnings are more less willing to share health rumor than friend warnings. Compared with hope rumor, the three forms of warning are more obvious to the reduction of fear rumor sharing willingness.
在线健康谣言,社交媒体,分享意愿,警告,群体参与, Online Health Rumors Social Media Sharing Intention Warnings Group Participation摘要
Research on the Influence of Adding Warnings on Different Types of Online Health Rumor Sharing Intention
Yuyu Wang
School of Management, Shanghai University of Engineering Science, Shanghai
Received: Aug. 7th, 2022; accepted: Aug. 29th, 2022; published: Sep. 13th, 2022
ABSTRACT
In view of the widespread spread of health rumors on social media platforms, add warnings to provide intervention suggestions to reduce the spread of online health rumors. Based on the information cascade theory and the negative bias theory, data analysis was performed in the SPSS 26.0 software, this paper uses the network scenario experiment to explore the impact of different forms of warnings on users’ willingness to share when the types of rumors are fear rumors and hope rumors respectively. The results show that adding warnings under health rumors can reduce users’ willingness to share. Compared with general user warnings, friend warnings and expert warnings reduce the willingness to share health rumors more significantly. Expert warnings are more less willing to share health rumor than friend warnings. Compared with hope rumor, the three forms of warning are more obvious to the reduction of fear rumor sharing willingness.
Keywords:Online Health Rumors, Social Media, Sharing Intention, Warnings, Group Participation
设在无警告状态下(对照组)人们对希望谣言的分享意愿为 Y 1 ,对恐惧谣言的分享意愿为 Y 2 ,三种警告类型分别为 H , I 和 J ,且 H , I , J 在希望谣言中的影响力为 K 1 、 K 2 、 K 3 ,在恐惧谣言中的影响力为 K 4 、 K 5 、 K 6 ,希望谣言在受到 H , I 和 J 类警告后的分享意愿为 Y H 1 、 Y I 1 、 Y J 1 ,恐惧谣言在受到 H , I 和 J 类警告后的分享意愿为 Y H 2 、 Y I 2 、 Y J 2 ,根据线性回归分析则有
Y 1 + K 1 * H = Y H 1 Y 2 + K 4 * H = Y H 2
两式相减得 ( K 1 − K 4 ) H = ( Y H 1 − Y 1 ) − ( Y H 2 − Y 2 ) > 0
由于 H 为对谣言的警告,对谣言传播有干预作用,故能降低人们的分享意愿,即 H < 0 ,因此有 K 1 − K 4 < 0 , K 1 < K 4 ,所以警告 H 对恐惧谣言的影响大于希望谣言。同理有 K 2 < K 5 , K 3 < K 6 ,故警告 I 和 J 对恐惧谣言的影响也大于希望谣言。
王钰昱. 添加警告对不同类型在线健康谣言分享意愿的影响研究Research on the Influence of Adding Warnings on Different Types of Online Health Rumor Sharing Intention[J]. 应用数学进展, 2022, 11(09): 6288-6297. https://doi.org/10.12677/AAM.2022.119664
参考文献ReferencesChua, A.Y.K. and Banerjee, S. (2017) To Share or Not to Share: The Role of Epistemic Belief in Online Health Rumors. International Journal of Medical Informatics, 108, 36-41. <br>https://doi.org/10.1016/j.ijmedinf.2017.08.010位志广, 宋小康, 朱庆华, 沈超, 张玥. 基于随机森林的健康谣言分享意愿研究[J]. 现代情报, 2020, 40(5): 78-87.Nagler, R.H. (2014) Adverse Outcomes Associated with Media Exposureto Contradictory Nutrition Mes-sages. Journal of Health Communication, 19, 24-40. <br>https://doi.org/10.1080/10810730.2013.798384Lin, H.C. and Chang, C.M. (2018) What Motivates Health Information Exchange in Social Media? The Roles of the Social Cognitive Theory and Perceived Interactivity. Information & Management, 55, 771-780.
<br>https://doi.org/10.1016/j.im.2018.03.006Ecker, U.K.H., Hogan, J.L. and Lewandowsky, S. (2017) Remind-ers and Repetition of Misinformation: Helping or Hindering its Retraction? Journal of Applied Research in Memory and Cognition, 6, 185-192.
<br>https://doi.org/10.1016/j.jarmac.2017.01.014Ecker, U.K.H., Lewandowsky, S. and Tang, D.T.W. (2010) Ex-plicit Warnings Reduce but Do Not Eliminate the Continued Influence of Misinformation. Memory & cognition, 38, 1087-1100. <br>https://doi.org/10.3758/MC.38.8.1087Linden S. (2022) Misinformation: Susceptibility, Spread, and Interventions to Immunize the Public. Nature Medicine, 28, 460-467. <br>https://doi.org/10.1038/s41591-022-01713-6Pennycook, G., Bear, A., Collins, E.T. and Rand, D.G. (2020) The Implied Truth Effect: Attaching Warnings to a Subset of Fake News Headlines Increases Perceived Accuracy of Headlines without Warnings. Management Science, 66, 4944-4957. <br>https://doi.org/10.1287/mnsc.2019.3478Difonzo, N., Robinson, N.M., Suls, J.M. and Rini, C. (2012) Ru-mors about Cancer: Content, Sources, Coping, Transmission, and Belief. Journal of Health Communication: Internation-al Perspectives, 17, 1099-1115.
<br>https://doi.org/10.1080/10810730.2012.665417Knapp, R.H.A (1944) Psychology of Rumor. Public Opinion Quarterly, 8, 22-37. <br>https://doi.org/10.1086/265665Shibutani, T. (1966) Improvised News. Ardent Media, London.Zhang, Y., Su, Y., Li, W. and Liu, H.O. (2018) Rumor and Authoritative Information Propagation Model Considering Super Spreading in Complex Social Networks. Physica A: Statistical Mechanics and Its Applications, 506, 395-411.
<br>https://doi.org/10.1016/j.physa.2018.04.082Zubiaga, A., Liakata, M., Procter, R., Wong Sak Hoi, G. and Tolmie, P. (2016) Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads. PLOS ONE, 11, Article ID: e0150989.
<br>https://doi.org/10.1371/journal.pone.0150989宋小康, 赵宇翔, 宋士杰, 朱庆华. 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.王晰巍, 邱程程, 贾若男. 突发公共卫生事件网络谣言辟谣效果影响因素研究——以新冠疫情期间网络谣言为例[J]. 图书情报工作, 2021, 65(19): 26-35.Jin, J.H., Yan, X.B., Li, Y.J. and Li, Y.M. (2016) How Users Adopt Healthcare Information: An Empirical Study of an Online Q&A Community. International Journal of Medical Informatics, 86, 91-103.
<br>https://doi.org/10.1016/j.ijmedinf.2015.11.002吴世文, 王一迪, 郑夏. 可信度的博弈:伪健康信息与纠正性信息的信源及其叙事[J]. 全球传媒学刊, 2019, 6(3): 73-91.张星, 吴忧, 夏火松. 在线健康谣言的传播意愿研究——谣言来源、类型和传播对象的作用[J]. 南开管理评论, 2020, 23(1): 200-212.Chua, A.Y.K. and Banerjee, S. (2018) Intentions to Trust and Share Online Health Rumors: An Experiment with Medical Professionals. Computers in Human Behavior, 87, 1-9. <br>https://doi.org/10.1016/j.chb.2018.05.021Chua, A.Y.K. and Banerjee, S. (2015) Analyzing Users’ Trust for Online Health Rumors. International Conference on Asian Digital Li-braries, Seoul, 9-12 December 2015, 33-38. <br>https://doi.org/10.1007/978-3-319-27974-9_4Pal, A., Chua, A.Y.K. and Goh, H.L. (2020) How Do Users Respond to Online Rumor Rebuttals? Computers in Human Behavior, 106, Article ID: 106243. <br>https://doi.org/10.1016/j.chb.2019.106243Grabowski, A., Wojciszke, B. and Broemer, P. (2005) Ambivalence of Attitudes towards People with Whom the Contact Is Closed or Continued. Polish Psychological Bulletin, 36, 99-107.唐雪梅, 赖胜强. 公共卫生安全事件中网络健康谣言的转发研究——感知风险与信息可信度的交互效应[J]. 情报杂志, 2021, 40(9): 101-107.Sunstein, C.R. (2014) On Rumors: How Falsehoods Spread, Why We Believe Them, and What Can Be Done. Princeton University Press, Princeton.Wang, Q., Yang, X. and Xi, W. (2018) Effects of Group Arguments on Rumor Belief and Transmission in Online Communities: An In-formation Cascade and Group Polarization Perspective. Information & Management, 55, 441-449.
<br>https://doi.org/10.1016/j.im.2017.10.004Thai, D.H. and Wang, T. (2020) Investigating the Effect of Social Endorsement on Customer Brand Relationships by Using Statistical Analysis and Fuzzy Set Qualitative Comparative Analysis (fsQCA). Computers in Human Behavior, 113, Article ID: 106499. <br>https://doi.org/10.1016/j.chb.2020.106499Liao, W., Zhang, Y. and Peng, X. (2019) Neurophysiological Ef-fect of Exposure to Gossip on Product Endorsement and Willingness-to-Pay. Neuropsychologia, 132, Article ID: 107123.
<br>https://doi.org/10.1016/j.neuropsychologia.2019.107123Jin, X.L., Yin, M., Zhou, Z. and Yu, X.Y. (2021) The Differential Effects of Trusting Beliefs on Social Media Users’ Willingness to Adopt and Share Health Knowledge. Information Processing & Management, 58, Article ID: 102413.
<br>https://doi.org/10.1016/j.ipm.2020.102413