The influence of group intelligence on individual decision-making under the condition of false health advertising information

Lü Ning, Xia Zhijie

Knowledge Management Forum ›› 2024, Vol. 9 ›› Issue (1) : 30-42.

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PDF(1492 KB)
Knowledge Management Forum ›› 2024, Vol. 9 ›› Issue (1) : 30-42. DOI: 10.13266/j.issn.2095-5472.2024.003

The influence of group intelligence on individual decision-making under the condition of false health advertising information

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Abstract

[Purpose/Significance] The widespread dissemination of false health information will bring unpredictable risks to public health. Exploring the impact of online social learning on public perceptions of false health information identification, sharing and false propaganda can help the public make rational health decisions and promote the governance of false health information from the perspective of social learning. [Method/Process] Through designing the experiment, the verified false health information was selected as the experimental material, and the influence of online social learning on the public's identification and confidence level of false health information was analyzed by using paired sample T test, independent sample T test and single factor ANOVA test. Moreover, the factors affecting the public sharing behavior were explored by using linear regression. [Result/Conclusion] The results showed that online social learning can improve the public's ability to distinguish false health information and enhanced the affirmation of self-judgment. The more transparent the user's background information, the better the risk cognition ability. At the same time, the degree of information authenticity has no significant effect on users' sharing behavior. Therefore, relevant suggestions are provided to provide theoretical reference for social media platforms to deal with false health information governance.

Key words

false health information / online social learning / information judgment / social media platform

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Lü Ning , Xia Zhijie. The influence of group intelligence on individual decision-making under the condition of false health advertising information[J]. Knowledge Management Forum. 2024, 9(1): 30-42 https://doi.org/10.13266/j.issn.2095-5472.2024.003

References

[1]
罗坤瑾,陈丽帆.事实核查:社交媒体虚假新闻治理研究[J].中国编辑,2020(8):42-46.(LUO K J, CHEN L F. Fact check: research on social media fake news governance [J]. Chinese editors journal,2020(8):42-46.)
[2]
WOLFE C, EYLEM A, DANDIGNAC M, et al. Understanding the landscape of Web-based medical misinformation about vaccination[EB/OL]. [2023-07-31]. https://link.springer.com/article/10.3758/s13428-022-01840-5.
[3]
DU J, PRESTON S, SUN H, et al. Using machine learning–based approaches for the detection and classification of human papillomavirus vaccine misinformation: infodemiology study of reddit discussions[EB/OL]. [2023-08-03]. https://www.jmir.org/2021/8/e26478.
[4]
TASHTOUSH Y, ALRABABAH B, DARWISH O, et al. A deep learning framework for detection of COVID-19 fake news on social media platforms[EB/OL]. [2023-08-04]. https://www.mdpi.com/2306-5729/7/5/65.
[5]
HAOUARI F, ELSAYED T, MANSOUR W. Who can verify this? finding authorities for rumor verification in Twitter[J]. Information processing & management,2023,60(4): 103366.
[6]
TURAN N, ÖZDEMIR N G, ÇULHA Y, et al. The effect of undergraduate nursing students’ e-Health literacy on healthy lifestyle behaviour[J].Global health promotion,2020,28(3):6-13.
[7]
HUI H, ZHOU C, LÜ X, et al. Spread mechanism and control strategy of social network rumors under the influence of COVID-19[J]. Nonlinear dynamics, 2020, 101(3):1933-1949.
[8]
GLASDAM S, STJERNSWÄRD S. Information about the COVID-19 pandemic–a thematic analysis of different ways of perceiving true and untrue information[J]. Social sciences & humanities open,2020,2(1):1-10.
[9]
杨洸,闻佳媛.微信朋友圈的虚假健康信息纠错:平台、策略与议题之影响研究[J].新闻与传播研究,2020,27(8):26-43,126. (YANG G, WEN J Y. Health misinformation correction on Wechat moments: the impacts platform strategies and issues [J]. Journalism & communication, 2020,27(8):26-43,126.)
[10]
张亦文.消费者社会化学习、个体认知与在线消费决策各阶段效率的互动关系[J].商业经济研究,2022(4):81-84.(ZHANG Y W. The interactive relationship between consumer social learning, individual cognition and efficiency at each stage of online consumption decision-making [J]. Journal of commercial economics,2022(4):81-84.)
[11]
ROITERO K, SOPRANO M, PORTELLI B, et al. The COVID-19 infodemic: can the crowd judge recent misinformation objectively?[C]// D’AQUIN M, DIETZE S, HAUFF C, et.al. Proceedings of the 29th ACM international conference on information & knowledge management. New York: ACM, 2020: 1305-1314.
[12]
ROITERO K, SOPRANO M, PORTELLI B, et al. Can the crowd judge truthfulness? A longitudinal study on recent misinformation about COVID-19[J]. Personal and Ubiquitous Computing, 2023,27(1):59–89.
[13]
熊回香,孟璇,叶佳鑫.新冠疫情虚假健康信息研究主题与核心要素研究综述[J].图书情报工作,2023,67(7):135-149.(XIONG H X, MENG X, YE J X. A review of research themes and core elements of false health information research on COVID-19 [J]. Library and information service, 2023,67(7):135-149.)
[14]
PATEK A. Diagnostic misinformation at a health resort[J]. Journal of the American Medical Association, 1912, 59(22): 1990-1991.
[15]
BINGER C. Medical information and misinformation[J]. Mental hygiene, 1947, 31(1): 1-13.
[16]
HUENEMANN R. Combating food misinformation and quackery[J]. Journal of the American Dietetic Association, 1956, 32(7): 623-626.
[17]
EBBINGHOUSE C. Medical and legal misinformation on the internet[J]. Searcher, 2000, 8(9): 18-27.
[18]
杨再华.伪健康传播与公民媒介素养[J].新闻记者,2005(4):56-58.(YANG Z H. Pseudo health communication and citizen media literacy [J]. Shanghai journalism review, 2005(4):56-58.)
[19]
WARDLE C. Fake news. it’s complicated[EB /OL].[2023-02-12].https://medium.com /1st-draft/fake-news-its-complicated-d0f773766c79.
[20]
朱宏淼,齐佳音,靳祯,等.医联网环境下失真健康信息传播动力学模型与干预策略研究[J].系统工程理论与实践,2022,42(7):1927-1940.(ZHU H M, QI J Y, JIN Z, et al. Research on distorted health information transmission dynamics model and intervention strategy in internet of healthcare system[J]. Systems engineering-theory & practice, 2022,42(7):1927-1940.)
[21]
宋士杰,赵宇翔,朱庆华.社交媒体中失真健康信息的传播、识别与纠偏研究[J].情报杂志,2023,42(6):162-169.(SONG S J, ZHAO Y X, ZHU Q H. A Comprehensive Review on health misinformation dissemination, identification and correction in social media [J]. Journal of intelligence, 2023,42(6):162-169.)
[22]
金燕,徐何贤,毕崇武.多维特征融合的虚假健康信息识别方法研究:基于LightGBM算法[J].情报理论与实践,2023,46(8):156-164.(JIN Y, XU H X, BI C W. Research on health misinformation identification method based on multi-dimensional feature fusion: based on lightgbm algorithm [J]. Information studies: theory & application, 2023,46(8):156-164.)
[23]
乔沛昕,董玉琦.社会化学习对学生学习成效的影响研究——基于47项实验和准实验研究的元分析[J].湖南师范大学教育科学学报,2023,22(1):51-65.(QIAO P X, DONG Y Q. A research of the influence of social learning on students' learning effectiveness——a meta-analysis based on 47 experimental and quasi-experimental studies[J]. Journal of Educational Science of Hunan Normal University, 2023,22(1):51-65.)
[24]
TROUSSAS C, KROUSKA A, SGOUROPOULOU C. Impact of social networking for advancing learners’ knowledge in E-learning environments[J]. Education and Information Technologies,2021,26:4285-4305.
[25]
DUAN J J, LU L , XIE K. Examining knowledge construction in three social interactive learning environments: a comparison of knowledge networks, social networks, and social knowledge networks[J]. Interactive learning environments,2021,31(6): 3914-3938.
[26]
GUILBEAULT D, CENTOLA D. Networked collective intelligence improves dissemination of scientific information regarding smoking risks[J].PLoS ONE,2020,15(2): e0227813.
[27]
王淑颖,张建雄,唐万生.考虑社会学习及成本学习的新体验品定价[J].管理科学学报,2023,26(2):36-48.(WANG S Y, ZHANG J X, TANG W S. Pricing of new experience goods considering social learning and cost learning [J]. Journal of management sciences in China, 2023,26 (2): 36-48)
[28]
何艺璇,闫文捷.谁在社交媒体扩散虚假健康信息?——健康素养与分析性思维的作用[J].新闻记者,2021(7):72-85.(HE Y X, YAN W J. Who spreads false health information on social media—— The role of health literacy and analytical thinking [J]. Shanghai journalism review, 2021(7): 72-85)
[29]
BALL P, MAXMEN A. The epic battle against coronavirus misinformation and conspiracy theories[J]. Nature,2020,581(7809):371-375.
[30]
WILLIAMSON P. Take the time and effort to correct misinformation[J]. Nature, 2016,540(7632):171.
[31]
PANGARKAR A, RATHEE S. The role of conspicuity: impact of social influencers on purchase decisions of luxury consumers[J]. International journal of advertising,2022,42(7):1150-1177.
[32]
ZHENG C, SONG Y, MA Y. Public opinion prediction model of food safety events network based on BP neural network[J]. IOP conference series: materials science and engineering, 2020, 719:012078.
[33]
TONI G L A, JIN Y. Seeking formula for misinformation treatmentin public health crises: the effects of corrective information type and source[J].Health communication,2020,35(5) :560-575.
[34]
上海市场监管. 曝光!2023年第一批虚假违法广告典型案例[EB/OL] . [2023-08-22]. https://mp.weixin.qq.com/s/e9ux7pXdgjKjM4Dg4HUp5Q .(Shanghai Market Regulation. Exposure! The first batch of typical cases of false and illegal advertising in 2023 [EB/OL]. [2023-08-22]. https://mp.weixin.qq.com/s/e9ux7pXdgjKjM4Dg4HUp5Q.)
[35]
阮文翠,夏志杰.社交媒体用户分享辟谣信息意愿的影响因素分析[J].科学与管理,2020,40(2):39-44.(RUAN W C, XIA Z J. Analysis of influencing factors of social media users' willingness to share counter-rumors [J]. Science and management, 2020,40 (2): 39-44)
[36]
TUREL O, OSATUYI B. Biased credibility and sharing of fake news on social media: considering peer context and self-objectivity state[J]. Journal of management information systems ,2021,38(4): 931-958
[37]
SCHERER L D, MCPHETRES J, PENNYCOOK G, et al. Who is susceptible to online health misinformation? a test of four psychosocial hypotheses[J]. Health Psychology, 2021,40(4):274-284.
[38]
GUR F A, MCLARTY B D, MULDOON J. The Sherifs’ contributions to management research[J].Journal of management history, 2017,23(2): 191-216.
[39]
PENNYCOOK G, RAND D G. The psychology of fake news[J]. Trends in cognitive sciences,2021,25(5):388-402.
[40]
CHON M G. Coping with mental health issues via communicative action in the digital age: testing cybercoping models[J]. Journal of communication in healthcare,2022, 15(4):289-299.

吕 柠:确定论文主题,撰写论文;

夏志杰:指导研究思路,修改论文。

Funding

National Social Science Fund of China titled “Research on Intelligent Governance Mechanism and Operation Strategy of Internet Rumors Supported by Big Data”(21BGL243)
Shanghai Philosophy and Social Science Planning titled “Research on Dissemination Characteristics of Pseudo-health Information and Multi-agent Collaborative Intervention in the Era of Big Data”(2020BGL005)
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