[Purpose/significance] This paper aims to sort out the research progress of network public opinion, which helps to clarify the internal relationship and theme evolution path among the knowledge base, transmission law, early warning mechanism and governance strategy of network public opinion research. [Method/process] Firstly, this paper analyzed the theoretical knowledge basis of network public opinion. Then, according to the law of content progression, the research of network public opinion was divided into four themes: influencing factors, transmission path, early warning mechanism and guiding governance strategy. Content analysis and social network analysis were used to analyze the topic correlation and explore the evolution path of network public opinion. [Result/conclusion] The results show that life cycle theory, cognitive set theory, silence spiral, group polarization theory, butterfly effect theory and governance theory are often used as the theoretical knowledge basis of network public opinion research. In addition, the network media environment, social structure pressure, netizens’ psychology, trigger events, effective mobilization and social control force are regarded as the important factors influencing the evolution of network public opinion. Moreover, the six themes of online public opinion, public opinion events, social media, stakeholders, big data and information dissemination are closely related to other research contents, and they play an important bridging role in the evolution path of themes.
[1] MINGYI G, RENWEI Z. A research on social network information distribution pattern with Internet public opinion formation[J]. Journalism & communication,2009,16(5):72-78.
[2] CHEN X, DUAN S. Research on clustering analysis of Internet public opinion[J]. Cluster computing, 2019,22(6):5997-6007.
[3] 王来华,冯希莹.舆情概念认识中的两个基本问题[J].天津社会科学,2012(6):73-76.
[4] ROUSSEAU J-J. Du contrat social (1762)[M]. Oeuvres Completes, III, Paris:Gallimard, 1964.
[5] BURSTEIN P. Bringing the public back in:should sociologists consider the impact of public opinion on public policy?[J]. Social forces,1988,77(1):27-62.
[6] WATTS D J, DODDS P S. Influentials, networks, and public opinion formation[J]. Journal of consumer research, 2007, 34(4):441-458.
[7] 谭伟.网络舆论概念及特征[J].湖南社会科学,2003(5):188-190.
[8] 王来华."舆情"问题研究论略[J].天津社会科学,2004(2):78-81.
[9] 王兰成,陈立富.国内外网络舆情演化、预警和应对理论研究综述[J].图书馆杂志,2018,37(12):4-13.
[10] 夏火松,甄化春.大数据环境下舆情分析与决策支持研究文献综述[J].情报杂志,2015,34(2):1-6,21.
[11] 李纲,陈璟浩.突发公共事件网络舆情研究综述[J].图书情报知识,2014(2):111-119.
[12] 付业勤,郑向敏.国内外网络舆情研究的回顾与展望[J].编辑之友,2013(12):56-58.
[13] LIU Y, ZHU J, SHAO X, et al. Diffusion patterns in disaster-induced internet public opinion:based on a Sina Weibo online discussion about the ‘Liangshan fire’ in China[J]. Environmental hazards, 2020,20:163-187.
[14] D'ANDREA E, DUCANGE P, BECHINI A, et al. Monitoring the public opinion about the vaccination topic from tweets analysis[J]. Expert systems with applications, 2019,116:209-226.
[15] 廖海涵,王曰芬,关鹏.微博舆情传播周期中不同传播者的主题挖掘与观点识别[J].图书情报工作,2018,62(19):77-85.
[16] 高承实,陈越,荣星,等.网络舆情几个基本问题的探讨[J].情报杂志,2011,30(11):52-56.
[17] 毕宏音.现代舆情研究十年历程的回顾和反思[J].天津社会科学,2013(4):67-71.
[18] 孔建华.国内网络舆情治理研究综述[J].电子政务,2018(12):67-78.
[19] 王国华,方付建.我国舆情信息工作体系建设:现状、困境、走向[J].图书情报工作,2010,54(6):36-39.
[20] 曾润喜.我国网络舆情研究与发展现状分析[J].图书馆学研究,2009(8):2-6.
[21] 胡峰.重大疫情网络舆情演变机理及跨界治理研究——基于"四点四阶段"演化模型[J].情报理论与实践,2020,43(6):23-29,55.
[22] 曾润喜,王晨曦,陈强.网络舆情传播阶段与模型比较研究[J].情报杂志,2014,33(5):119-124.
[23] PETERSEN M B, SZNYCER D, COSMIDES L, et al. Who deserves help? Evolutionary psychology, social emotions, and public opinion about welfare[J]. Political psychology,2012.33(3):395-418.
[24] 乐国安,李绍洪.心理定势发生机制的模型建构[J].心理学探新,2006(2):3-8.
[25] 王兰成,陈立富.国内外网络舆情演化、预警和应对理论研究综述[J].图书馆杂志,2018,37(12):4-13.
[26] 张丽君, 黄明涛. 边疆民族地区网络民族舆情治理探索——以"整体治理"理论为基础[J].广西民族研究,2019(1):54-64.
[27] 余亮.网络舆情形成的影响因素分析[J].西南农业大学学报(社会科学版),2013,11(6):177-180.
[28] ZHAO Y. Public opinion evolution based on complex networks[J]. Cybernetics & information technologies, 2015, 15(1):55-68.
[29] 马翔,包国宪.网络舆情事件中的公共价值偏好与政府回应绩效[J].公共管理学报,2020,17(2):70-83,169.
[30] 徐勇. 网络舆情事件演变的动力学建模及预警监测[J].现代情报, 2016,36(4):14-19,56.
[31] 王筱纶, 顾洁. 企业危机网络舆情的传播路径及其在供应链中的纵向溢出效应研究[J].管理科学,2019,32(1):46-59.
[32] 侯萍, 刘海洋. 社交媒体用户舆情传播行为的影响因素分析[J]. 电子商务,2019(1):51-53,59.
[33] 王来华.当前舆情研究深入展开中的几个重要问题[J].新闻与传播研究,2018,25(1):120-121.
[34] MOSTAFA M M. More than words:Social networks' text mining for consumer brand sentiments[J]. Expert systems with applications, 2013, 40(10):4241-4251.
[35] 赵宬斐."网络集群行为"与"价值累加"——一种集体行动的逻辑与分析[J].新闻与传播研究,2013,20(8):67-77,127.
[36] 许敏.网络群体性事件研究:路径、视角与方法[J].甘肃社会科学,2013,(4):61-64.
[37] 易承志. 群体性突发事件网络舆情的演变机制分析[J].情报杂志, 2011,30(12):6-12.
[38] 廖卫民. 论突发事件中的舆论动员——以南方雪灾为例[J].新闻记者,2008(4):9-12.
[39] 徐敬宏,李欲晓,方滨兴,等.非常规突发事件中网络舆情的生成及管理[J].当代传播,2010(4):41-43.
[40] 刘毅. 网络舆情研究概论[M]. 天津:天津人民出版社,2007.
[41] 谢耘耕,荣婷.微博舆论生成演变机制和舆论引策略[J].现代传播(中国传媒大学学报),2011(5):70-74.
[42] 宋姜,吴鹏,甘利人.网络舆情建模方法研究述评[J].图书情报工作,2014, 58(19):136-143.
[43] ALLAN J. Topic detection and tracking:event-based information organization[M]. German:Springer Science & Business Media,2012.
[44] 刘雯, 高峰, 洪凌子.基于情感分析的灾害网舆情研究——以雅安地震为例[J].图书情报工作,2013,57(20):104-110.
[45] 余秀才.网络舆情研究中的大数据技术使用与题[J].新闻大学, 2017(2):112-118.
[46] 戴媛,姚飞.基于网络舆情安全的信息挖掘及评估指标体系研究[J].情报理论与实践, 2008,31(6):873-876.
[47] 曾润喜.网络舆情突发事件预警指标体系构建[J].情报理论与实践, 2010,33(1):77-80.
[48] 王青,成颖,巢乃鹏.网络舆情监测及预警指标体系研究综述[J].情报科学,2011,29(7):1104-1108.
[49] 李文静.舆情应对的评价指标体系及其构建[J].重庆社会科学,2017(5):103-111.
[50] 瞿志凯,张秋波,兰月新,等.暴恐事件网络舆情风险预警研究[J].情报杂志, 2016,35(6):40-46.
[51] 张宇,傅敏,罗加蓉.震灾网络舆情风险监测指标及其评估方法[J].重庆大学学报(社会科学版),2018,24(6):33-44.
[52] 刘健,毕强,李瑞.微博舆情信息传播效果评价指标体系构建研究——基于模糊数据包络分析法[J].情报理论与实践,2016,39(12):31-38.
[53] 黄微,徐烨,刘熠,等.多媒体网络舆情衰退期形成的评估指标体系构建研究[J].情报理论与实践,2020,43(1):76-81.
[54] 李维安,陈春花,张新民,等.面对重大突发公共卫生事件的治理机制建设与危机管理——"应对新冠肺炎疫情"专家笔谈[J].经济管理,2020,42(3):8-20,5.
[55] 余晓宏,王先俊.微媒体时代政府舆情信息聚合发展趋势研究[J].情报科学,2020,38(7):173-177.
[56] 王丹,张海涛,刘嫣,等.全景生态视角的微博舆情多维图谱构建研究[J].情报学报,2019,38(12):1275-1285.
[57] 笪蕾.全媒体时代网络舆情治理研究[J].人民论坛·学术前沿,2020(9):108-111.
[58] 李维安,张耀伟,孟乾坤.突发疫情下应急治理的紧迫问题及其对策建议[J].中国科学院院刊,2020,35(3):235-239.
[59] 刘奕.以大数据筑牢公共卫生安全网:应用前景及政策建议[J].改革,2020(4):5-16.