•  
  •  
 

Journal of Scientific Information Research

Keywords

social media platform; scientific knowledge; science communication; knowledge demand measurement; factor analysis; entropy method

Abstract

[Purpose/significance] Exploring the scientific knowledge demand of netizens on social media platform will prompt the dissemination and utilization of scientific knowledge, and it plays an important role in enhancement of the scientific literacy level of our general publics.

[Method/process] This paper constructed a measurement index system of netizens' scientific knowledge demand consists of demand breadth, demand strength and demand hierarchy, and adopted a comprehensive evaluation method based upon factor analysis and entropy method. 30 popular science WeChat accounts in different fields are measured and evaluated, and the comprehensive ranking of demand was calculated to explore and compare the demand differences among different types of scientific knowledge.

[Result/conclusion] The results show that daily life knowledge and medical knowledge dominate in both demand breadth and demand strength. In contrast, humanities and social sciences knowledge, engineering technology knowledge and natural biological knowledge have relative advantages in different dimensions of demand hierarchy.

First Page

91

Last Page

102

Submission Date

March 2025

Revision Date

April 2025

Acceptance Date

April 2025

Publication Date

October 2025

Digital Object Identifier (DOI)

ꎺ 10.19809/j.cnki.kjqbyj.2025.04.009

Reference

[1] 国务院. 国务院关于印发全民科学素质行动规划纲要 (2021—2035年) 的通知[EB/OL]. (2021-06-25) [2025-3-04]. https://www.gov.cn/zhengce/content/2021-06/25/content_5620813.htm.
[2] 科技部. 科技部发布2023年度全国科普统计数据[EB/OL]. (2014-12-18) [2024-12-30]. https://www.most.gov.cn/kjbgz/201412/t20141218_117008.html.
[3] 刘杨, 吴玉莹. 基于微信公众号的科普信息移动化传播策略研究: 以“我是科学家iScientist”为例[J]. 新闻爱好者, 2021 (4): 45-48.
[4] 徐琳琳, 李胜男. 自媒体中的科学传播异化问题探析[J]. 科技传播, 2021, 13 (20): 53-55.
[5] 郑博临. 我国科学传播研究的脉络演进 (1998-2020): 基于科学知识图谱的可视化分析[J]. 文化与传播, 2021, 10 (2): 54-59.
[6] 钱斌, 张想. 基于受众需求的网络科普发展研究[J]. 重庆邮电大学学报 (社会科学版), 2020, 32 (5): 101-107.
[7] 李敏. 基因编辑技术媒介形象的传播与建构: 以微信公众号为考察对象[J]. 昆明理工大学学报 (社会科学版), 2021, 21 (2): 106-114.
[8] 景谷玥. 后疫情时代科学传播面临的挑战与应对策略[J]. 科技传播, 2021, 13 (5): 15-17.
[9] 黄静茹. 科学内容短视频传播: 现状、功能与反思[J]. 电视研究, 2021 (7): 87-90.
[10] 展威震, 易凯谕, 胡宝琨. 新媒体环境下的科学传播研究: 以微信为例[J]. 新闻研究导刊, 2016, 7 (7): 90.
[11] WESTERMAN D, SPENCE P R, VAN DER HEIDE B. Social media as information source: Recency of updates and credibility of information[J]. Journal of Computer‐Mediated Communication, 2014, 19 (2): 171-183.
[12] 孙凤. 科普型网红走红背后的文化品味[J]. 人民论坛, 2021 (36): 110-113.
[13] 金兼斌, 江苏佳, 陈安繁, 等. 新媒体平台上的科学传播效果: 基于微信公众号的研究[J]. 中国地质大学学报 (社会科学版), 2017, 17 (2): 107-119.
[14] MASAHARU T, YOSUKE O, TORII H A, et al. Twitter use in scientific communication revealed by visualization of information spreading by influencers within half a year after the Fukushima Daiichi nuclear power plant accident[J]. Plos One, 2018, 13 (9): e0203594.
[15] TAO Z Y, CHU G, MCGRATH C, et al. Nature and diffusion of COVID-19-related oral health information on Chinese social media: analysis of tweets on weibo[J]. Journal of Medical Internet Research, 2020, 22 (6): e19981.
[16] TIMILSINA M, M D'AQUIN, YANG H. Heat diffusion approach for scientific impact analysis in social media[J]. Social Network Analysis&Mining, 2019, 9 (1): 16.
[17] WELBOURNE D J, GRANT W J. Science communication on YouTube: Factors that affect channel and video popularity[J]. Public Understanding of Science, 2015, 25 (6): 706-718.
[18] 徐萌, 展进涛. 我国农户科学知识的需求层次、获取渠道及其提升策略分析[J]. 科技管理研究, 2013, 33 (15): 266-270.
[19] 晁亚男, 毕强, 滕广青. 高校学生用户开放存取知识需求分析[J]. 中国图书馆学报, 2013, 39 (1): 63-70.
[20] 张向先, 李中梅, 郭顺利. 社会化问答社区用户知识需求及其动态演化研究[J]. 情报理论与实践, 2018, 41 (11): 38-44, 50.
[21] 郭顺利, 孙笑, 宋拓, 等. 用户需求驱动下社会化问答社区知识聚合服务研究[J]. 情报科学, 2021, 39 (2): 106-113, 136.
[22] 朱静. 个人知识需求层次模型及个人知识管理与知识服务策略[J]. 图书情报工作, 2008, 52 (S2): 108-110, 26.
[23] WANG L, ZHONG Q. Research on the Structures and Features of Netizens' Demand for Popular Science: A Search Data Perspective[J]. Cultures of Science, 2019, 2 (2): 129-150.
[24] 张铁男, 赵健宇, 袭希. 组织知识创造的能级跃迁模型研究[J]. 管理工程学报, 2013, 27 (4): 41-52.
[25] 庄彩云, 陈福集. 基于霍尔三维结构的政府网络舆情知识需求分析[J]. 图书馆学研究, 2015 (6): 53-58, 45.
[26] 毛刚, 吕晓声, 李贺. 基于社会知识论和需求理论的学科间理论交叉研究[J]. 图书情报知识, 2013 (3): 96-102.
[27] 王黎明, 钟琦. 基于搜索数据的网民科普需求结构和特征研究[J]. 科普研究, 2018, 13 (4): 51-60, 107-108.
[28] 张建勇, 李宁, 张晓林. 文献资源整合化建设的思路和实践[J]. 图书情报工作, 2008, 52 (9): 116-119, 147.
[29] 郑方辉, 梁伟湖. 需求导向与推动高质量发展政绩考评: 一种理论诠释[J]. 行政论坛, 2021, 28 (6): 43-50.
[30] 王国辉, 付少平. 农民对农业科技知识需求强度的实证研究: 以杨凌示范区为典型个案[J]. 西北农林科技大学学报 (社会科学版), 2010, 10 (3): 8-12.
[31] 胡媛, 黄依琳. 网络用户社会化信息搜寻能力实证研究[J]. 现代情报, 2017, 37 (3): 73-78, 108.
[32] 王润. 知识付费产品发展反思: 以“得到”和“喜马拉雅”APP为例[J]. 中国出版, 2019 (22): 53-56.
[33] 高悦. 科协在推进科普体系建设中的问题及对策研究[D]. 长春: 吉林大学, 2013.
[34] 郑建程, 韩新月. 数字资源引进中的用户需求分析与评价方法[J]. 现代情报, 2007 (9): 18-21.
[35] 成文胜. 传统媒体时政类微信公众账号的运营模式探析[J]. 当代传播, 2015 (5): 62-67.
[36] 徐盛. 高校图书馆信息服务满意度调研分析[D]. 哈尔滨: 黑龙江大学, 2016.
[37] 单晓红, 张晓月, 刘晓燕. 基于在线评论的用户画像研究: 以携程酒店为例[J]. 情报理论与实践, 2018, 41 (4): 99-104, 149.
[38] 党明辉. 公共舆论中负面情绪化表达的框架效应: 基于在线新闻跟帖评论的计算机辅助内容分析[J]. 新闻与传播研究, 2017, 24 (4): 41-63, 127.
[39] 严纯. 微信“看一看”中的自我想象与他人认同[J]. 新闻传播, 2019 (18): 29-30.
[40] KATZ E, BLUMLER J, GUREVITCH M. Utilization of mass communication by the individual[J]. The Uses of Mass Communications: Current Perspectives on Gratifications Research, 1974: 19-32.
[41] 程子轩. 面向用户知识需求的微信公众平台知识资源聚合及服务研究[D]. 长春: 吉林大学, 2021.
[42] JUNG A R. The influence of perceived ad relevance on social media advertising: Anempirical examination of a mediating role of privacy concern[J]. Computers in Human Behavior, 2017, 70 (5): 303-309.
[43] 李琪. 科学谣言网络传播的情感驱动机制研究[D]. 沈阳: 辽宁大学, 2021.
[44] SHI S, CHEN Y, CHOW W S. Key values driving continued interaction on brand pages in social media: An examination across genders[J]. Computers in Human Behavior, 2016, 62 (Sep): 578-589.
[45] VRIES L D, GENSLER S, LEEFLANG P. Popularity of Brand Posts on Brand Fan Pages: An Investigation of the Effects of Social Media Marketing[J]. Journal of Interactive Marketing, 2012, 26 (2): 83-91.
[46] PRIYADARSHINI C, SREEJESH S, ANUSREE M R. Effect of information quality of employment website on attitude toward the website: A moderated mediation study[J]. International Journal of Manpower, 2017, 38 (5): 729-745.
[47] JUNG Y, PEREZ-MIRA B, WILEY-PATTON S. Consumer adoption of mobile TV: Examining psychological flow and media content[J]. Computers in Human Behavior, 2009, 25 (1): 123-129.
[48] PE-THAN E P P, GOH H L, LEE C S. Making work fun: Investigating antecedents of perceived enjoyment in human computation games for information sharing[J]. Computers in Human Behavior, 2014, 39 (10): 88-99.
[49] FLANAGIN A J, WINTER S, METZGER M J. Making sense of credibility incomplex information environments: the role of message sidedness, information source, and thinking styles in credibility evaluation online[J]. Information, Communication&Society, 2020, 23 (7): 1038-1056.
[50] JAMALI H R, Nikzad M. Article title type and its relation with the number of downloads and citations[J]. Scientometrics, 2011, 88 (2): 653-661.
[51] YANG S, LI S, LING Z, et al. Emotion mining research on micro-blog[C]//IEEE Symposium on Web Society. IEEE, 2009.
[52] 秦琴, 柯青, 丁松云. 中文在线健康教育信息可读性计算及应用实证: 以食品安全领域为例[J]. 现代情报, 2020, 40 (5): 111-121.
[53] 方婧, 陆伟. 微信公众号信息传播热度的影响因素实证研究[J]. 情报杂志, 2016, 35 (2): 157-162.
[54] 廖伯琴, 杨玉梅. 西南民族地区 “互联网+科普” 现状及影响因素调查研究[J]. 民族教育研究, 2021, 32 (6): 100-106.

Download

Share

COinS