|
|
Factors that Influence the Dissemination Effects of Short Videos of Refuting Rumors Based on Heuristic-Systematic Model |
Fu Shaoxiong1,2, Su Yiqi1, Sun Jianjun2 |
1.College of Information Management, Nanjing Agricultural University, Nanjing 210095 2.School of Information Management, Nanjing University, Nanjing 210023 |
|
|
Abstract The key to refuting rumors on short video platforms is to enhance the dissemination of short videos refuting rumors. To improve the dissemination effect of short videos refuting rumors and deepen the ecological governance of network information, we analyzed the influence of content design and posting techniques for short videos refuting rumors on their dissemination. This study manually coded 965 official disinformation videos on TikTok. Based on the heuristic-systematic model, heuristic (posting techniques) and systematic (central and peripheral content) cues were contextualized within a short video platform, and the number of likes, comments, favorites, and shares were used as indicators of dissemination effectiveness to analyze the effect of heuristic-systematic cues on dissemination. The results of the regression analysis indicate that the number of likes, topic types in heuristic cues, information completeness, information uniqueness, title symbols and modal diversity in systematic cues had significant effects; for the number of collections, duration, posting time period, topic types and background music volatility in heuristic cues, information completeness, information uniqueness, title styles, and title symbols in systematic cues had significant effects; for the number of comments, posting time period and background music volatility in heuristic cues, information uniqueness and title symbols in systematic cues had significant effects; for the number of shares, posting time period and the linkage in heuristic cues, information uniqueness and the way of information presentation in systematic cues had significant effects. This study extends the research perspective of short videos refuting rumors, expands the research context of the heuristic-systematic model, and clarifies the factors that influence the dissemination effects of short videos refuting rumors.
|
Received: 09 March 2023
|
|
|
|
1 打击谣言、治理算法……2022年“清朗”系列专项行动将重点整治这些网络乱象[EB/OL]. (2022-03-17) [2023-01-05]. http://www.gov.cn/xinwen/2022-03/17/content_5679589.htm. 2 中国互联网络信息中心. 第51次《中国互联网络发展状况统计报告》[EB/OL]. (2023-03-02) [2023-03-08]. https://www.cnnic.net.cn/n4/2023/0303/c88-10757.html. 3 QuestMobile. 2022中国移动互联网发展年鉴(整体篇)[EB/OL]. (2022-12-13) [2024-03-26]. https://36kr.com/p/2041856212897026. 4 朱梦蝶, 付少雄, 郑德俊, 等. 文献视角下的社交媒体健康谣言研究: 特征、传播与治理[J]. 图书情报知识, 2022, 39(5): 131-143. 5 王品芝, 高卿雯. 眼见未必为实! 小视频成谣言传播新渠道[N/OL]. 中国青年报, 2018-11-20(7). [2023-01-05]. http://zqb.cyol.com/html/2018-11/20/nw.D110000zgqnb_20181120_1-07.htm. 6 王超. 辟谣何以失灵?——一个信息传播效果视角的解释框架[J]. 情报杂志, 2019, 38(5): 123-129. 7 易明, 张雪, 李梓奇. 社交网络中辟谣信息传播效果的影响因素研究[J]. 情报科学, 2022, 40(5): 3-10, 18. 8 陈娟, 刘燕平, 邓胜利. 政务微博辟谣信息传播效果的影响因素研究[J]. 情报科学, 2018, 36(1): 91-95, 117. 9 韩旭, 李阳. 突发事件情境下社交媒体辟谣信息传播效果影响因素研究[J]. 情报理论与实践, 2022, 45(8): 97-103. 10 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. 11 Zhao L M, Yin J L, Song Y. An exploration of rumor combating behavior on social media in the context of social crises[J]. Computers in Human Behavior, 2016, 58: 25-36. 12 Li Z M, Zhang Q, Du X Y, et al. Social media rumor refutation effectiveness: evaluation, modelling and enhancement[J]. Information Processing & Management, 2021, 58(1): 102420. 13 Tripathy R M, Bagchi A, Mehta S. Towards combating rumors in social networks: models and metrics[J]. Intelligent Data Analysis, 2013, 17(1): 149-175. 14 Takayasu M, Sato K, Sano Y, et al. Rumor diffusion and convergence during the 3.11 earthquake: a Twitter case study[J]. PLoS One, 2015, 10(4): e0121443. 15 Chaiken S. Heuristic versus systematic information processing and the use of source versus message cues in persuasion[J]. Journal of Personality and Social Psychology, 1980, 39(5): 752-766. 16 Tam K Y, Ho S Y. Web personalization as a persuasion strategy: an elaboration likelihood model perspective[J]. Information Systems Research, 2005, 16(3): 271-291. 17 Chaiken S, Ledgerwood A. A theory of heuristic and systematic information processing[M]// Handbook of Theories of Social Psychology. London: SAGE Publications, 2012: 246-266. 18 Trumbo C W. Information processing and risk perception: an adaptation of the heuristic-systematic model[J]. Journal of Communication, 2002, 52(2): 367-382. 19 Zhang K Z K, Zhao S J, Cheung C M K, et al. Examining the influence of online reviews on consumers' decision-making: a heuristic-systematic model[J]. Decision Support Systems, 2014, 67: 78-89. 20 Shi S, Gong Y H, Gursoy D. Antecedents of trust and adoption intention toward artificially intelligent recommendation systems in travel planning: a heuristic-systematic model[J]. Journal of Travel Research, 2021, 60(8): 1714-1734. 21 陈明红, 黄涵慧. 基于HSM的移动搜索行为影响因素及组态效应研究[J]. 图书情报工作, 2021, 65(20): 68-80. 22 Ebrahimi S, Ghasemaghaei M, Benbasat I. The impact of trust and recommendation quality on adopting interactive and non-interactive recommendation agents: a meta-analysis[J]. Journal of Management Information Systems, 2022, 39(3): 733-764. 23 Luo X, Zhang W, Burd S, et al. Investigating phishing victimization with the heuristic-systematic model: a theoretical framework and an exploration[J]. Computers & Security, 2013, 38: 28-38. 24 Kim S E, Lee K Y, Shin S I, et al. Effects of tourism information quality in social media on destination image formation: the case of Sina Weibo[J]. Information & Management, 2017, 54(6): 687-702. 25 唐亚阳, 陈三营. 高校官方微信公众号传播效果影响因素的实证研究——基于启发-系统模型[J]. 湖南大学学报(社会科学版), 2018, 32(5): 155-160. 26 杜松华, 柯晓波, 后锐, 等. 基于HSM的企业微信影响力研究: 以P2P网贷平台为例[J]. 管理评论, 2016, 28(12): 198-212. 27 宁海林, 羊晚成. 重大突发公共卫生事件传播效果的影响因素实证分析——以卫健类抖音政务号为例[J]. 现代传播(中国传媒大学学报), 2021, 43(1): 147-151. 28 吴江, 马芸芸, 蔡婧璇. MOOC平台用户知识获取意愿影响因素研究[J]. 情报科学, 2021, 39(9): 50-58. 29 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. 30 李永宁, 吴晔, 杨濮宇, 等. 内容为王: 社交短视频平台的知识传播机制研究[J]. 新闻与写作, 2019(6): 23-32. 31 Welbourne D J, Grant W J. Science communication on YouTube: factors that affect channel and video popularity[J]. Public Understanding of Science, 2016, 25(6): 706-718. 32 赵璐. 算法实践的社会建构——以某信息分发平台为例[J]. 社会学研究, 2022, 37(4): 23-44, 226-227. 33 黄楚新. 融合背景下的短视频发展状况及趋势[J]. 人民论坛·学术前沿, 2017(23): 40-47, 85. 34 Scherr S, Wang K X. Explaining the success of social media with gratification niches: motivations behind daytime, nighttime, and active use of TikTok in China[J]. Computers in Human Behavior, 2021, 124: 106893. 35 张志安, 彭璐. 混合情感传播模式: 主流媒体短视频内容生产研究——以人民日报抖音号为例[J]. 新闻与写作, 2019(7): 57-66. 36 赵辰玮, 刘韬, 都海虹. 算法视域下抖音短视频平台视频推荐模式研究[J]. 出版广角, 2019(18): 76-78. 37 黄晓音, 邱子昊. 技术赋能与情感互动: 抖音平台的视觉化音乐传播研究[J]. 西南民族大学学报(人文社科版), 2019, 40(8): 156-161. 38 李露琪, 侯丽, 邓胜利. 突发公共卫生事件网络虚假信息传播行为影响因素研究——以新冠疫情期间微博虚假信息为例[J]. 图书情报工作, 2022, 66(9): 4-13. 39 张玉琪, 郭斌, 丁亚三, 等. 社交网络假消息辟谣作用机理[J]. 浙江大学学报(工学版), 2021, 55(4): 615-625. 40 李俊霆. 辟谣信息的文本结构和叙事框架——以中国互联网联合辟谣平台为例[D]. 西安: 西北大学, 2021: 17-30. 41 刘中刚. 双面信息对辟谣效果的影响及辟谣者可信度的调节作用[J]. 新闻与传播研究, 2017, 24(11): 49-63, 127. 42 吕美霞, 王磊. 高校图书馆与公共图书馆微信公众平台比较研究[J]. 图书情报工作, 2019, 63(13): 52-65. 43 沈丽红. 图书馆热门短视频内容规律探究——基于抖音平台的实证研究[J]. 图书馆, 2020(12): 75-82. 44 郁建兴, 吴昊岱, 沈永东, 等. 脱钩改革如何影响行业协会商会政策参与?——基于795家全国性商协会的实证研究[J]. 管理世界, 2022, 38(9): 145-157. 45 储节旺, 吴若航. 公共图书馆短视频营销效果影响因素研究——基于省级馆的调查[J]. 情报科学, 2022, 40(12): 13-21. 46 张舒涵, 孔朝蓬, 孔婧媛. 新媒体时代短视频信息传播影响力研究[J]. 情报科学, 2021, 39(9): 59-66. 47 谢敏. 抖音算法与爆款短视频打造研究[J]. 传媒, 2022(24): 52-54. 48 姜景, 王文韬. 面向突发公共事件舆情的政务抖音研究——兼与政务微博的比较[J]. 情报杂志, 2020, 39(1): 100-106, 114. 49 张永芹. 短视频媒介火爆的背后: 建设性新闻理念的实践——以“抖音”手机软件为例[J]. 当代传播, 2020(5): 59-62. 50 徐琦, 罗雪丹. 从中心化辟谣到人机协同: 中国网络辟谣平台的范式升级——基于1228条新冠疫情辟谣数据[J]. 全球传媒学刊, 2021, 8(3): 85-101. 51 高晓晶, 喻梦倩, 杨家燕, 等. 图书馆短视频传播及互动效果影响因素模型及实证分析——基于“上瘾模型”的探索[J]. 图书情报工作, 2021, 65(10): 13-22. 52 前瞻产业研究院. 2023年中国短视频行业竞争格局及市场份额分析 抖音和快手的竞争排名较强[EB/OL]. (2023-01-13) [2023-05-04]. https://bg.qianzhan.com/trends/detail/506/230113-ff8326b2.html. 53 Neter J, Kutner M H, Nachtsheim C J, et al. Applied linear statistical models[M]. Chicago: Irwin, 1996. 54 抖音安全中心. 谣言传播背后的真相,我们帮你总结出来了[EB/OL]. (2022-04-20) [2023-01-05]. https://www.toutiao.com/article/7088593936876585486/?wid=1669811306686. 55 贾碧筱. 网络谣言排行榜研究: 内容属性、谣言再现与辟谣实践[D]. 武汉: 武汉大学, 2019: 50-52. 56 熊炎. 辟谣信息构成要素: 一种整合框架——二战以后西方辟谣实证研究回顾[J]. 国外社会科学, 2015(1): 78-88. 57 谢娟, 李文文, 沈鸿权, 等. 信息爆炸和信息不确定语境下的可信度判据研究——以COVID-19疫情为例[J]. 情报学报, 2021, 40(7): 714-724. 58 唐雪梅, 赖胜强, 刘家瑶, 等. 社会化媒体用户信息转发的研究述评[J]. 情报杂志, 2022, 41(7): 131-137. 59 陆颖颖, 易明, 李梓奇, 等. 基于人类动力学的微博用户评论行为研究[J]. 情报科学, 2023, 41(2): 157-168. 60 付少雄, 袁秋, 邓胜利, 等. 承诺理论视角下辟谣短视频分享意愿的驱动因素[J/OL]. 图书馆论坛, (2023-09-21) [2023-09-22]. https://kns.cnki.net/kcms/detail/44.1306.G2.20230921.1037.002.html. 61 吴诗苑, 董庆兴, 宋志君, 等. 社交媒体中错误信息的检测方法研究述评[J]. 情报学报, 2022, 41(6): 651-661. 62 付少雄, 孙岚, 邓胜利, 等. 应对理论视角下短视频用户虚假健康信息采纳的动因研究[J]. 情报资料工作, 2023, 44(6): 100-110. 63 王晰巍, 张柳, 黄博, 等. 基于区块链的网络谣言甄别模型及仿真研究[J]. 情报学报, 2021, 40(2): 194-203. 64 孙建军, 裴雷, 付少雄. 兼收并蓄: 信息资源管理学科建设背景下的数据管理[J]. 信息资源管理学报, 2023, 13(1): 9-17. |
|
|
|