[1]孙玉艳徐子杨.社交媒体虚假信息转发机理研究[J].信息化理论与实践,2022,02(02):49-59.
　A study on the mechanism of social media disinformation forwarding Xu ziyang1 Sun yunyan2[J].Information Theory and Practice,2022,02(02):49-59.
点击复制

社交媒体虚假信息转发机理研究()
分享到：

《信息化理论与实践》[ISSN:2520-5862/CN:]

卷:
02
期数:
2022年02
页码:
49-59
栏目:
出版日期:
2023-12-30

文章信息/Info

Title:
A study on the mechanism of social media disinformation forwarding Xu ziyang1 Sun yunyan2
作者:
102;  102); font-family: Arial;  Verdana;  sans-serif; font-size: 12px; background-color: rgb(255;  255;  255);">孙玉艳1 徐子杨2
1(福州大学图书馆 福州 350000)
Author(s):
1
(Library, Fuzhou University, Fuzhou 35000, China) 2 ( Library, Minjiang University, Fuzhou 35000, China)
关键词:
社交媒体 虚假信息 转发机理
Keywords:
Social media Disinformation Forwarding mechanism
摘要:
目的]当前社交媒体平台上发布的消息真假难辨，尤其2019年新冠疫情爆发后，各类谣言甚嚣尘上。本文旨在基于用户视角探索社交媒体虚假信息的转发机理和行为特征，验证影响用户转发影响因素，从而对减轻社交媒体虚假信息的危害，对净化网络环境、提升社交媒体公信力等具有积极的实践意义。[方法]基于此，本文结合SOR模型，对收集到的270份有效问卷采用结构方程模型分析，考察影响用户虚假信息的转发行为因素。[结果]结果表明，信息内容对感知有用性和信任程度存在正向影响，信息源特征对信任程度存在正向影响。信息的感知有用性和用户的信任程度对虚假信息的转发行为具有正向影响；信息的感知风险性对虚假信息的转发行为具有显著的负向影响。因此，要想控制虚假信息的传播，就要从源头遏制虚假信息传播，进一步完善监督管理制度和及时辟谣。
Abstract:
[Objective] At present, it is difficult to distinguish between true and false news of all kinds on social media platforms, especially after the outbreak of COVID-19, various kinds of rumours have become widespread. The purpose of this paper is to explore the mechanism of forwarding false information in social media based on users’ perspective, and to verify the influencing factors affecting users’ forwarding, so as to alleviate the harm of false information in social media, and have positive practical significance for purifying the online environment and improving the credibility of social media. [Methods] this paper combines the SOR model with structural equation modelling analysis on 270 valid questionnaires collected to examine the factors influencing users’ forward behaviour of false information. [Results] The results show that there is a positive influence of information content on perceived usefulness and trust level, and a positive influence of information source characteristics on trust level. The perceived usefulness of information and the trust level of users have a positive influence on the forwarding behaviour of disinformation; the perceived riskiness of information has a significant negative influence on the forwarding behaviour of disinformation. Therefore, in order to control the spread of false information, it is necessary to curb the spread of false information at source, further improve the supervision and management system and timely disinformation.

参考文献/References:

[1] 苏鹏, 王延飞. 对信息迷雾的情报观察:概念、形成与应对[J]. 情报理论与实践, 2021,44(3): 6-12.

[2] 涂念. 公共危机事件中微博信息可信度的影响因素研究[D]. 成都：电子科技大学, 2015.

[3] 王剑, 王玉翠, 黄梦杰. 社交网络中的虚假信息：定义、检测及控制[J]. 计算机科学, 2021,48(8): 263-277.

[4] PAL A, CHUA A Y K, HOE-LIAN GOH D. Debunking rumors on social media: The use of denials[J]. Computers in Human Behavior, 2019,96: 110-122.

[5] MEHRABIAN A R J A. An Approach to Environmental Psychology[G]. Cambridge:MIT Press, 1974.

[6] 王义保, 王天宇, 刘卓, 等. 基于SOR模型的突发公共卫生事件公众应急行为研究[J]. 重庆社会科学, 2020(5): 19-31.

[7] 郑美玉. 基于SOR框架的手机图书馆用户持续使用影响因素研究[J]. 图书馆工作与研究, 2018(4): 52-58.

[8] 刘遗志, 胡争艳, 汤定娜. 多渠道零售环境下消费者在线渠道迁徙意愿研究——基于SOR理论模型视角[J]. 大连理工大学学报(社会科学版), 2022,43(1): 38-49.

[9] YADAV N, VERMA S, CHIKHALKAR R D. eWOM, destination preference and consumer involvement – a stimulus-organism-response (SOR) lens[J]. Tourism Review, 2021,ahead-of-print(ahead-of-print).

[10] DERAKHSHAN H. INFORMATION DISORDER : Toward an interdisciplinary framework for research and policy making Information Disorder Toward an interdisciplinary framework for research and policymaking[M]. Council of Europe, 2017.

[11] YE P, LIU L. Factors influencing college students’ behaviours of spreading internet public opinions on emergencies in universities[J]. Information Discovery and Delivery, 2021,50(1): 75-86.

[12] OH O, GUPTA P, AGRAWAL M, et al. ICT mediated rumor beliefs and resulting user actions during a community crisis[J]. Government Information Quarterly, 2018,35(2): 243-258.

[13] SHARMA A, KAPOOR P S. Message sharing and verification behaviour on social media during the COVID-19 pandemic: a study in the context of India and the USA[J]. Online Information Review, 2021,46(1): 22-39.

[14] 廖琳, 黄涛. 信源、信息内容、情绪特征对微博转发的影响探究[J]. 现代情报, 2020,40(9): 42-52.

[15] 刘春年, 张凌宇. 融合风险感知的应急网站信息服务质量跨层次交互效应分析[J]. 现代情报, 2016,36(6): 27-34.

[16] ZHOU C, XIU H, WANG Y, et al. Characterizing the dissemination of misinformation on social media in health emergencies: An empirical study based on COVID-19[J]. Information Processing & Management, 2021,58(4): 102554.

[17] 高雅. 微博新闻事件信息可信度评价[D]. 长春：吉林大学, 2013.

[18] 徐珊珊. 突发事件下微博用户转发行为影响因素研究[D]. 哈尔滨：黑龙江大学, 2019.

[19] 张旸, 路荣, 杨青. 微博客中转发行为的预测研究[J]. 中文信息学报, 2012,26(4): 109-114, 121.

[20] DAVIS F D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology[J]. MIS Quarterly, 1989,3(13): 319-340.

[21] APUKE O D, OMAR B. Fake news and COVID-19: modelling the predictors of fake news sharing among social media users[J]. Telematics and Informatics, 2021,56: 101475.

[22] AVEN T. Risk assessment and risk management: Review of recent advances on their foundation[J]. European Journal of Operational Research, 2016,253(1): 1-13.

[23] ALEMANY J, DEL VAL E, ALBEROLA J, et al. Enhancing the privacy risk awareness of teenagers in online social networks through soft-paternalism mechanisms[J]. International Journal of Human-Computer Studies, 2019,129: 27-40.

[24] GARDNER D E. Risk communication and non-linearity[J]. Human & Experimental Toxicology, 2009,28(1): 27.

[25] GARRETT R K. Troubling Consequences of Online Political Rumoring[J]. Human communication research, 2011,37(2): 255-274.

[26] CHUNG N, NAM K, KOO C. Examining information sharing in social networking communities Applying theories of social capital and attachment[J]. Telematics and Informatics, 2016,1(33): 77-91.

[27] 王琳, 马子乔. 新冠肺炎疫情下大学生的信息焦虑研究——基于应激障碍水平的视角[J]. 现代情报, 2020,40(7): 14-24.

[28] 熊爽. 微信朋友圈信息转发行为的需求因素研究[D]. 广州：暨南大学, 2016.

[29] 厉钟灵. 微博用户转发意愿研究——基于感知信息质量视角[D]. 杭州：浙江大学, 2012.

[30] LIU L, TANG J, HAN J, et al. Learning Influence from Heterogeneous Social Networks[J]. DATA MINING AND KNOWLEDGE DISCOVERY, 2012,3(25): 511-544.

[31] 黄楚新, 朱常华. 短视频在突发公共事件中的功能与作用——以新冠肺炎疫情信息传播为例[J]. 视听界, 2020(2): 55-59.

[32] 孙会, 李丽娜. 高频次转发微博的特征及用户转发动机探析——基于新浪微博“当日转发排行榜”的内容分析[J]. 现代传播(中国传媒大学学报), 2012,34(6): 137-138.

[33] 王傲, 刘宝瑞. 虚拟社区知识共享过程中的知识信任度研究[J]. 情报科学, 2012,30(9): 1328-1333.

[34] 金晓玲, 金可儿, 汤振亚, 等. 微博用户在突发事件中转发行为研究:基于信息源的视角[J]. 情报学报, 2015,34(8): 809-818.

[35] HA S, AHN J. Why are you sharing others’tweets?: The impact of argument quality and source credibility on information sharing behavior.: CIS 2011 Proceedings[C], 2011.

[36] 胡欣阅. 小红书滤镜事件的三维剖析[J]. 新闻研究导刊, 2022,13(4): 112-114.

更新日期/Last Update: 2024-06-20