How Long Does Agenda Setting Take? A Temporal Analysis of Media-Public Agenda Dynamics During Crisis Events Based on ARIMA Modeling
Keywords:
Time series, ARIMA model, Agenda setting, Granger causality analysis, Public opinion managementAbstract
The decentralized digital media landscape has diversified agenda-setting actors, creating challenges like misinformation and emotional amplification that complicate crisis communication. This study investigates the temporal dynamics of traditional media, social media, and public agendas during crisis events, using the Cathay Pacific incident as a representative case of transnational media discourse. Drawing on agenda-setting theory and the public opinion lifecycle model, it applies ARIMA time-series modeling, social network analysis, and Granger causality testing to analyze interactions and lag structures among communication actors across different stages of crisis evolution. Empirically, the study identifies a distinct 40-hour lag between the peak agenda-setting effectiveness of social and traditional media during the early phase of public opinion formation. Social media demonstrated the highest temporal responsiveness within the first 24 hours, with its influence declining after the sixth day, whereas traditional media exhibited delayed but sustained impact on the agenda. These findings reveal that agenda-setting operates through recursive, time-sensitive influence cycles rather than linear dissemination. By integrating theoretical refinement and practical relevance, this study advances temporal agenda-setting research through the quantification of cross-platform lag interactions and the modeling of bidirectional media–public dynamics. The findings further inform crisis communication management, underscoring the need for synchronized cross-platform timing and proactive interventions to preempt misinformation and foster rational public discourse
References
Alamsyah, A. (2024). Framing Gibran's Vice Presidential Candidacy: A Gioia Model Analysis of Media Influence on Public Opinion in Political Communication. CHANNEL: Jurnal Komunikasi, 12(2), 103–116. https://doi.org/10.12928/channel.v12i2.749
Albalawi, Y., & Sixsmith, J. (2015). Agenda setting for health promotion: exploring an adapted model for the social media era. JMIR public health and surveillance, 1(2), e5014. https://doi.org/10.2196/publichealth.5014
Aldamen, Y., & Hacimic, E. (2023). Positive determinism of Twitter usage development in crisis communication: Rescue and relief efforts after the 6 February 2023 earthquake in Türkiye. Social Sciences, 12(8), 436-450. https://doi.org/10.3390/socsci12080436
Arman, Z. R., & McClurg, S. (2024). Exploring the relationship between televised presidential debate and Twitter: A network analysis of intermedia agenda setting. Communication Studies, 75(2), 165–185. https://doi.org/10.1080/10510974.2024.2342062
Baharuddin, T., Sairin, S., & Nurmandi, A. (2022). Building social capital online during the COVID-19 transition in Indonesia. Jurnal Komunikasi, 42(1), 56-71. https://doi.org/10.25008/jkiski.v7i1.607
Bennett, W. L., & Segerberg, A. (2012). The logic of connective action: Digital media and the personalization of contentious politics. Information, Communication & Society, 15(5), 739-768. https://doi.org/10.1017/cbo9781139198752
Blinder, S. (2015). Imagined immigration: The impact of different meanings of 'immigrants' in public opinion and policy debates in Britain. Political Studies, 63(1), 80-100. https://doi.org/10.1111/1467-9248.12053
Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (2015). Time series analysis: Forecasting and control. John Wiley & Sons.
Breuer, A., & Spring, U. O. (2020). The 2030 Agenda as Agenda Setting Event for Water Governance? Evidence from the Cuautla River Basin in Morelos and Mexico. Water, 12(2), 314. https://doi.org/10.3390/w12020314
Conway, B. A., Kenski, K., & Wang, D. (2015). The rise of Twitter in the political campaign: Searching for intermedia agenda-setting effects in the presidential primary. Journal of Computer-Mediated Communication, 20(4), 363-380. https://doi.org/10.1111/jcc4.12124
Daud, R. S. (2021). The role of political communication in shaping public opinion: A comparative analysis of traditional and digital media. Journal of Public Representative and Society Provision, 1(3), 24–36. https://doi.org/10.55885/jprsp.v1i2.241
De Gooijer, J. G., & Hyndman, R. J. (2006). 25 years of time series forecasting. International Journal of Forecasting, 22(3), 443-473. https://doi.org/10.1016/j.ijforecast.2006.01.001
Ding, B. (2023). A preliminary discussion on the guidance of online public opinion: A study of guidance strategies. Journal of Northwest Normal University (Social Sciences), 60(3), 86–95. https://doi.org/10.16783/j.cnki.nwnus.2023.03.010
Dusi, N., & Lacalle, C. (2024). Chernobyl calling. Narrative, intermediality and cultural memory of a docu-fiction. IRIS - University of Modena and Reggio Emilia,5-17.
Feezell, J. T. (2018). Agenda setting through social media: The importance of incidental news exposure and social filtering in the digital era. Political Research Quarterly, 71(2), 482–494. https://doi.org/10.1177/1065912917744895
Fink, S. (1986). Crisis management: Planning for the inevitable. American Management Association.
Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791
Guo, L., & McCombs, M. (2016). The power of information networks: New directions for agenda-setting. Journalism & Mass Communication Quarterly, 93(3), 441-461. https://doi.org/10.4324/9781315726540
Guo, M., & Yang, J. (2023). Inverted conduction: The obscured public opinion ditch in the perspective of reverse agenda-setting—Taking the Tangshan beating incident as an example. Journalism, 10, 52-63. https://doi.org/10.15897/j.cnki.cn51-1046/g2.20230927.002
Hidayat, M. N., Fahrianoor, & Siswanto. (2024). Exploring the Role of Social Media in Disaster Management: A Case Study of the 2021 South Kalimantan Flood. CHANNEL: Jurnal Komunikasi, 12(2), 117–128. https://doi.org/10.12928/channel.v12i2.847.
Ju, Y. (2008). The asymmetry in economic news coverage and its impact on public perception in South Korea. International Journal of Public Opinion Research, 20(2), 237–249. https://doi.org/10.1093/ijpor/edn021
Karpf, D. (2012). The MoveOn Effect: The Unexpected Transformation of American Political Advocacy. Oxford University Press.
Katz, E., & Lazarsfeld, P. F. (1955). Personal influence: The part played by people in the flow of mass communications. Free Press.
Kim, C. M. (2016). Social Media Campaigns Strategies for Public Relations and Marketing. Routledge.
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York: Guilford Press.
Lütkepohl, H. (2005). New introduction to multiple time series analysis. Berlin: Springer. https://doi.org/10.1007/978-3-540-27752-1
McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176–187. https://doi.org/10.1086/267990
Mo, Z., Zhao, Y., & Wang, K. (2023). Evolutionary analysis of the dynamic game model of self-purification of false information in social media under sudden public events. Journal of Intelligence, 9, 98-108.
Neuman, W. R., Guggenheim, L., Jang, S. M., & Bae, S. Y. (2014). The dynamics of public attention: Agenda-setting theory meets big data. Journal of Communication, 64(2), 193–214. https://doi.org/10.1111/jcom.12088
Reynolds, B., & W Seeger, M. (2005). Crisis and emergency risk communication as an integrative model. Journal of health communication, 10(1), 43–55. https://doi.org/10.1080/10810730590904571
Riezebos, P., De Vries, S. A., de Vries, P. W., & De Zeeuw, E. (2011). The effects of social media on political party perception and voting behavior. In Proceedings of the IADIS International Conference e-Democracy, Equity and Social Justice, 7(20),11–19.
Roberts, M., Wanta, W., & Dzwo, T. H. (2002). Agenda setting and issue salience online. Communication research, 29(4), 452-465. https://doi.org/10.1177/00936502020290040
Salman, A., Mustaffa, N., Mohd Salleh, M. A., & Ali, M. N. S. (2016). Social media and agenda setting: Implications on political agenda. Malaysian Journal of Communication, 32(1), 607–623. https://doi.org/10.17576/JKMJC-2016-3201-35
Sunstein, C. R. (2014). On rumors: How falsehoods spread, why we believe them, and what can be done. Princeton University Press. https://doi.org/10.2307/j.ctv6zddck
Tandoc, E. C., Lim, Z. W., & Ling, R. (2017). Defining “Fake News”: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153. https://doi.org/10.1080/21670811.2017.1360143
Tang, J. T., & Chen, Q. Y. (2022). Application of time series data analysis in communication research. Contemporary Communication, 29-34.
Tong, J. (2025). Serving the public interest? A computational analysis of the topics of UK national newspaper coverage using Freedom of Information (FOI) requests between 2005 and 2020. Journalism Studies, 26(4), 521–540. https://doi.org/10.1080/1461670X.2025.2518453
Tufekci, Z (2017). Twitter and Tear Gas: The Power and Fragility of Networked Protest, New Haven: Yale University Press. https://doi.org/10.12987/9780300228175
Vargo, C. J., & Guo, L. (2016). Networks, big data, and intermedia agenda setting: An analysis of traditional, partisan, and emerging online U.S. news. Journalism & Mass Communication Quarterly, 94(4), 1031–1055. https://doi.org/10.1177/1077699016679976
Vargo, C. J., Guo, L., & Amazeen, M. A. (2017). The agenda-setting power of fake news: A big data analysis of the online media landscape from 2014 to 2016. New Media & Society, 23(8), 2042-2067. https://doi.org/10.1177/1461444817712086
Vonbun R, Königslöw K. K., & Schönbach K. (2016). Intermedia agenda-setting in a multimedia news environment. Journalism, 17(8), 1054-1073. https://doi.org/10.1177/1464884915595475.
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. science, 359(6380), 1146-1151. https://doi.org/10.1126/science.aap9559
Waisbord, S. (2018). Truth is What Happens to News: On journalism, fake news, and post-truth. Journalism Studies, 19(13), 1866–1878. https://doi.org/10.1080/1461670X.2018.1492881
Wang, H., & Yu, D. (2020). A study on intermedia agenda setting on the microblog platform: Based on the analysis of public opinion hot events in 2018. Journalism University, 6, 82-96, 125. https://doi.org/10.20050/j.cnki.xwdx.2020.06.010.
Weimann, G., & Brosius, H. B. (2017). Redirecting the agenda: Agenda-setting in the online Era. The Agenda Setting Journal, 1(1), 63-102. https://doi.org/10.1075/asj.1.1.06wei
Xiao, W. T., & Zeng, H. L. (2017). Response to governmental public opinion in emergencies: Facing the posture, predicament, and countermeasure ideas. China Administration, 12, 111-116.
Xie, Y., & Rong, T. (2011). The generation and evolution mechanisms of public opinion on Weibo and strategies for public opinion guidance. Modern Communication (Journal of Communication University of China), (5), 70–74. https://doi.org/10.19997/j.cnki.xdcb.2011.05.013
Yang, A., & Saffer, A. J. (2019). Embracing a network perspective in the network society: The dawn of a new paradigm in strategic public relations. Public Relations Review, 45(4), 545-561. https://doi.org/10.1016/j.pubrev.2019.101843
Zhang, Q., & Yan, J. (2018). Systematic analysis and path to good governance of online public opinion governance in China. Chinese Administration, 9, 21-29. https://doi.org/10.19735/j.issn.1006-0863.2018.09.03.
Zhang, S. Y., Fan, Z., & Guo, M. Y. (2014). Cointegration theory and volatility modeling: Financial time series analysis and applications. Tsinghua University Press.
Zhang, W. X. (2019). Be alert to the misunderstanding of public opinion governance behind the "seven-day law of communication." People's Forum, 28, 114-116.
Zhao, B., & Zhang, H. (2023). Time change in agenda setting: An analysis based on social bots, media, and public time lag. International Journalism, 2, 52-80. https://doi.org/10.13495/j.cnki.cjjc.2023.02.005.
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 CHANNEL: Jurnal Komunikasi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
