Current Status and Trends in Rumor Governance: A Visual Analysis based on CiteSpace

Authors

  • Zhixuan Zhang
  • Yi Zhang
  • Dandan Wang

DOI:

https://doi.org/10.62051/ijsspa.v6n2.19

Keywords:

CiteSpace, Online Rumors, Rumor Governance, Visual Analysis, Knowledge Mapping

Abstract

[Purpose/Significance] With the advent of the 5G era and the rapid development of the internet, the speed and modes of rumor dissemination have continuously evolved. This study employs bibliometric methods to conduct a systematic review and visual analysis of scholarly articles on rumor governance, aiming to clarify the research landscape, key features, hotspots, and future directions in this field. [Methods/Process] Utilizing data from the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) core databases, this study applies CiteSpace, a bibliometric analysis tool, to examine publication trends, highly cited authors, prolific researchers, keyword co-occurrence patterns, and thematic clusters from60 2012 to 2024. [Results/Conclusion] The findings indicate that foreign researchers exhibit high publication productivity and strong collaborative networks, whereas domestic researchers are relatively dispersed with weaker cooperative ties. Keyword co-occurrence and cluster analysis reveal that domestic research predominantly focuses on the practical implementation of governance strategies, emphasizing macro-level frameworks such as "collaborative governance," and primarily employing qualitative methodologies to propose policy recommendations and localized practices. In contrast, international studies prioritize the universality of communication models, utilizing quantitative methods and model construction to examine the micro-level mechanisms influencing individual behavior and collective emotions. Future research should integrate the contextual depth of case studies with the generalizability of quantitative models to explore user psychology, the long-term societal impacts of rumors, and the role of legal frameworks in rumor governance. Additionally, cross-cultural research should be expanded to analyze the mechanisms of rumor dissemination across different cultural contexts and governance models, addressing the challenges posed by the globalization of information dissemination.

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References

[1] Askarizadeh M, Ladani B T, Manshaei M H. An evolutionary game model for analysis of rumor propagation and control in social networks[J]. Physica A: statistical mechanics and its applications, 2019, 523: 21-39.

[2] LI B, YU G M. Discourse space and propagation field of Internet rumors in the post-Truth era: An analysis based on 4160 rumors in WeChat circle of Friends[J].Journalism Research, 2018,(02):103-112+121+153. DOI:10.20050/j.cnki.xwdx.2018.02.012.

[3] Chen J, Liu Y P, Deng S L. An analysis of factors influencing the dissemination effect of rumor-refuting information[J]. China. J. Information Science, 2018, 36(1): 91-95.

[4] Ren Y Q, Wang Y, Wang G. Research on the Evolution Mechanism of Micro-blog Rumors[J]. Journal of Intelligence, 2012, 31(5): 50-54.

[5] Mengfei T, Jiancheng W. A Research on Rumorsrefuting Effects of Government Micro-blog in Emergency Based on The Case Study of Shanghai Bund Stampede Incident[J]. Journal of Intelligence, 2015, 34(8): 36-98.

[6] Chen Y S. Research on the spread and control of online rumors in Public health Emergencies: Text analysis of online rumors based on the novel coronavirus epidemic[J]. E-Government, 2020,(06):2-11.DOI:10.16582/j.cnki.dzzw.2020.06.001

[7] Liu Z Y, Zhang L, Tu C, et al. Statistical and semantic analysis of rumors in Chinese social media[J]. Scientia Sinica Informationis, 2015, 45(12): 1536.

[8] Shengqiang L. Influencing mechanism of the Online Rumors on audiences’ re-transmission behavior[J]. Journal of Intelligence, 2014, 33(05): 153-156.

[9] Ma L, Ma C, Zhang H F, et al. Identifying influential spreaders in complex networks based on gravity formula[J]. Physica A: Statistical Mechanics and its Applications, 2016, 451: 205-212.

[10] Yang L, Li Z, Giua A. Containment of rumor spread in complex social networks[J]. Information Sciences, 2020, 506: 113-130.

[11] Shrivastava G, Kumar P, Ojha R P, et al. Defensive modeling of fake news through online social networks[J]. IEEE Transactions on Computational Social Systems, 2020, 7(5): 1159-1167.

[12] Li J, Jiang H, Mei X, et al. Dynamical analysis of rumor spreading model in a multi-lingual environment and heterogeneous complex networks[J]. Information Sciences, 2020, 536: 391-408.

[13] Chen Y S. Research on the spread and control of online rumors in Public health Emergencies: Text analysis of online rumors based on the novel coronavirus epidemic[J]. E-Government, 2020,(06):2-11.DOI:10.16582/j.cnki.dzzw.2020.06.001

[14] Li H Q. Research on evolution law and countermeasure of the derived network public opinion based on information alienation theory-taking internet rumors governance for example[J]. Journal of Modern Information, 2015, 35(5): 4-8.

[15] Depoux A, Martin S, Karafillakis E, et al. The pandemic of social media panic travels faster than the COVID-19 outbreak[J]. Journal of Travel Medicine, 2020, 27(3): taaa031.

[16] Islam M S, Sarkar T, Khan S H, et al. COVID-19–related infodemic and its impact on public health: A global social media analysis[J]. The American journal of tropical medicine and hygiene, 2020, 103(4): 1621.

[17] Wu Y K, Huang H, Wu Q, et al. A risk defense method based on microscopic state prediction with partial information observations in social networks[J]. Journal of Parallel and Distributed Computing, 2019, 131: 189-199.

[18] Liu W, Wu X, Yang W, et al. Modeling cyber rumor spreading over mobile social networks: A compartment approach[J]. Applied Mathematics and Computation, 2019, 343: 214-229.

[19] Lai S, Tang X. On the impact of emotional information on online rumor spread[J]. Journal of Intelligence, 2016, 35(1): 116-121.

[20] Zhu L, Wang B. Stability analysis of a SAIR rumor spreading model with control strategies in online social networks[J]. Information Sciences, 2020, 526: 1-19.

[21] Liang-an Huo, Fan Ding et al. Dynamical Analysis of Rumor Spreading Model Considering Node Activity in Complex Networks. Complexity. 2018, 2018. [SCI].

[22] Li J, Jiang H, Mei X, et al. Dynamical analysis of rumor spreading model in a multi-lingual environment and heterogeneous complex networks[J]. Information Sciences, 2020, 536: 391-408.

[23] Wang G, Waang Y J. The dissemination structure and influencing factors of rumor-refuting information in microblog platform[J/OL]. Journal of Intelligence, 1-8[2025-01-01].

[24] Yang Y Y. Research on information portrait and governance model of network refuting rumors under data drive -- based on tipping point theory[J/OL]. Information Science, 1-14[2025-01-20].

[25] Yang R B, Yin C X. Exploring the Combination Factors of Rumor Refutal Dissemination Effects on Social Media Platform: A Comparative Analysis Based on Multiple Contexts [J]. Library and Information Service, 2023,67(24):72-84.

[26] QIANR LI X LIU X Y, et al. Rumor Spreading Model Considering Prohibition Mechanism [J]. Computer Engineering, 2024,50(08):372-378.

[27] Li Z, Zhang Q, Du X. Research on rumor-refutation effectiveness based on the interactions and popular comments’ emotional tendencies of the rumor-refuting microblogs: taking rumor-refuting microblogs related with COVID-2019 as an example[J]. J. Intell, 2020, 39(11): 7.

[28] network method for Sina Weibo rumor detection[J]. Journal of Chinese Computer Systems, 2021,42(08):1780-1786)

[29] Huang W X, Kang G Q. The generation and governance of Internet rumors from the perspective of audience psychology: A case study of the "AIDS woman" incident[J]. Academic Journal of Zhongzhou, 2011,(02):255-258.

[30] Pennycook G, Rand D G. Fighting misinformation on social media using crowdsourced judgments of news source quality[J]. Proceedings of the National Academy of Sciences, 2019, 116(7): 2521-2526.

[31] Zeng R, Zhu D. A model and simulation of the emotional contagion of netizens in the process of rumor refutation[J]. Scientific Reports, 2019, 9(1): 14164.

[32] Bakshy E, Messing S, Adamic L A. Exposure to ideologically diverse news and opinion on Facebook[J]. Science, 2015, 348(6239): 1130-1132.

[33] Chen D B, Gao H, Lü L, et al. Identifying influential nodes in large-scale directed networks: the role of clustering[J]. PloS one, 2013, 8(10): e77455.

[34] Choi D, Chun S, Oh H, et al. Rumor propagation is amplified by echo chambers in social media[J]. Scientific Reports, 2020, 10(1): 310.

[35] Shah D, Zaman T. Rumors in a network: Who's the culprit?[J]. IEEE Transactions on Information Theory, 2011, 57(8): 5163-5181.

[36] Xiao Y, Chen D, Wei S, et al. Rumor propagation dynamic model based on evolutionary game and anti-rumor[J]. Nonlinear Dynamics, 2019, 95: 523-539.

[37] Jiang G, Li S, Li M. Dynamic rumor spreading of public opinion reversal on Weibo based on a two-stage SPNR model[J]. Physica A: Statistical Mechanics and its Applications, 2020, 558: 125005.

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Published

2025-03-11

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Articles

How to Cite

Zhang, Z., Zhang, Y., & Wang, D. (2025). Current Status and Trends in Rumor Governance: A Visual Analysis based on CiteSpace. International Journal of Social Sciences and Public Administration, 6(2), 149-162. https://doi.org/10.62051/ijsspa.v6n2.19