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Open Access

A Quantitative Analysis of the Relationship Between the Public and News Media Attentions to Hot Network Events in China

Jiaqing Liu1,2,Yue Wang2,( )Sha He3Wuyue Shangguan4Tianmei Wang2
School of Information, Renmin University of China, Beijing 100872, China
School of Information, Central University of Finance and Economics, Beijing 100081, China
LinkedIn Inc., Sunnyvale, CA 94085, USA
School of Management, Xiamen University, Xiamen 361005, China

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Abstract

With the popularity of new media, the relationship between the media and the public has changed considerably. A comprehensive and quantitative analysis of the relationship between the public and media can reveal the development of news media in China and help provide some constructive advice to improve their quality. Therefore, we establish vector autoregression (VAR) models between the media and the public on 160 network trending events from 2011 to 2018 based on the Baidu Index. In specific terms, we explore the causal relationship between them with the Granger causality test and analyze the dynamic effects using the impulse response function (IRF) analysis. Our findings suggest that there are satisfactory two-way interactions between the news media and the public in China (especially in the event categories directly related to people’s livelihood, such as safety misadventure, natural disasters, food and drug safety, and entertainment) and that the public plays a leading role for most events. We also find that the news media lags behind users generally, which prompts us to propose the three-relay hypothesis to explain its dissemination mechanism. Also, the impulse responses of attention to negative events are generally more drastic than those to positive events. For hot network events in China, the time span and sample size of our research are large, increasing the results’ reliability.

References

1
M. W. Ragas, H. L. Tran, and J. A. Martin, Media-induced or search-driven? A study of online agenda-setting effects during the BP oil disaster, Journalism Studies, vol. 15, no. 1, pp. 48–63, 2014.https://doi.org/10.1080/1461670X.2013.793509
2
W. R. Neuman, L. Guggenheim, S. M. Jang, and S. Y. Bae, The dynamics of public attention: Agenda-setting theory meets big data, Journal of Communication, vol. 64, no. 2, pp. 193–214, 2014.https://doi.org/10.1111/jcom.12088
3
M. T. Bastos, D. Mercea, and A. Charpentier, Tents, tweets, and events: The interplay between ongoing protests and social media, Journal of Communication, vol. 65, no. 2, pp. 320–350, 2015.https://doi.org/10.1111/jcom.12145
4
Baidu Index, http://index.baidu.com/Helper/, 2022.
5
B. Sayre, L. Bode, D. Shah, D. Wilcox, and C. Shah, Agenda setting in a digital age: Tracking attention to California proposition 8 in social media, online news and conventional news, Policy & Internet, vol. 2, no. 2, pp. 7–32, 2010.https://doi.org/10.2202/1944-2866.1040
6

Y. Peng, J. Li, H. Xia, S. Qi, and J. Li, The effects of food safety issues released by we media on consumers’ awareness and purchasing behavior: A case study in China, Food Policy, vol. 51, pp. 44–52, 2015.

7

K. A. Wibowo and S. Karlinah, Detroit water shutoff: The dynamics of intermedia agenda setting, Journal of Physics:Conference Series, vol. 1114, p. 012006, 2018.

8
Y. Ni, The impact of the development of American new media on citizens’ political power and life, in Proc. 2021 International Conference on Social Development and Media Communication (SDMC 2021), Sanya, China, 2021, pp. 905–909.https://doi.org/10.2991/assehr.k.220105.167
9
S. Yuan and R. Zhang, A systematic review of new media influencing people’s attitude and cognition to GMF, in Proc. 2021 International Conference on Social Development and Media Communication (SDMC 2021), Sanya, China, 2021, pp. 185–189.https://doi.org/10.2991/assehr.k.220105.036
10
L. Guggenheim, S. M. Jang, S. Y. Bae, and W. R. Neuman, The dynamics of issue frame competition in traditional and social media, The Annals of the American Academy of Political and Social Science, vol. 659, no. 1, pp. 207–224, 2015.https://doi.org/10.1177/0002716215570549
11

H. Rui and A. Whinston, Information or attention? An empirical study of user contribution on Twitter, Information Systems and E-Business Management, vol. 10, no. 3, pp. 309–324, 2012.

12
J. Groshek and M. C. Groshek, Agenda trending: Reciprocity and the predictive capacity of social networking sites in intermedia agenda setting across topics over time, SSRN Electronic Journal, vol. 1, no. 1, pp. 15–27, 2013.https://doi.org/10.17645/mac.v1i1.71
13
B. Zhang, J. Sun, H. Zhang, and C. Xu, Can promotion on WeChat official accounts improve scholarly journals’ academic impact? A micro-level correlation comparison study, Learned Publishing, vol. 35, no. 2, pp. 163–174, 2022.https://doi.org/10.1002/leap.1440
14
M. E. McCombs and D. L. Shaw, The agenda-setting function of mass media, Public Opinion Quarterly, vol. 36, no. 2, pp. 176–187, 1972.https://doi.org/10.1086/267990
15

M. McCombs, A look at agenda-setting: Past, present and future, Journalism Studies, vol. 6, no. 4, pp. 543–557, 2005.

16
S. Iyengar and D. R. Kinder, News That Matters: Television and American Opinion. Chicago, IL, USA: University of Chicago Press, 2010.https://doi.org/10.7208/chicago/9780226388601.001.0001
17

L. V. D. Heijkant and R. Vliegenthart, Implicit frames of CSR: The interplay between the news media, organizational PR, and the public, Public Relations Review, vol. 44, no. 5, pp. 645–655, 2018.

18
S. Y. Lee and D. Riffe, Who sets the corporate social responsibility agenda in the news media? Unveiling the agenda-building process of corporations and a monitoring group, Public Relations Review, vol. 43, no. 2, pp. 293–305, 2017.https://doi.org/10.1016/j.pubrev.2017.02.007
19

J. E. Uscinski, When does the public’s issue agenda affect the media’s issue agenda (and vice-versa)? Developing a framework for media-public influence, Social Science Quarterly, vol. 90, no. 4, pp. 796–815, 2009.

20
J. T. Ripberger, Capturing curiosity: Using internet search trends to measure public attentiveness, Policy Studies Journal, vol. 39, no. 2, pp. 239–259, 2011.https://doi.org/10.1111/j.1541-0072.2011.00406.x
21

S. Vosoughi, D. Roy, and S. Aral, The spread of true and false news online, Science, vol. 359, no. 6380, pp. 1146–1151, 2018.

22

S. Ghosh, M. -H. Su, A. Abhishek, J. Suk, C. Tong, K. Kamath, O. Hills, T. Correa, C. Garlough, P. Borah, et al., Covering #metoo across the news spectrum: Political accusation and public events as drivers of press attention, The International Journal of Press/Politics, vol. 27, no. 1, pp. 158–185, 2022.

23
J. Zhu, X. Wang, J. Qin, and L. Wu, Assessing public opinion trends based on user search queries: Validity, reliability, and practicality, in Proc. 65thAnnual Conf. of the World Association for Public Opinion Research, Hong Kong, China, 2012, pp. 1–7.
24
L. Kristoufek, Bitcoin meets Google trends and Wikipedia: Quantifying the relationship between phenomena of the internet era, Scientific Reports, vol. 3, no. 1, p. 3415, 2013.https://doi.org/10.1038/srep03415
25

S. Dastgir, E. Demir, G. Downing, G. Gozgor, and C. K. M. Lau, The causal relationship between bitcoin attention and bitcoin returns: Evidence from the copula-based granger causality test, Finance Research Letters, vol. 28, pp. 160–164, 2019.

26
L. Vaughan and Y. Chen, Data mining from web search queries: A comparison of google trends and baidu index, Journal of the Association for Information Science and Technology, vol. 66, no. 1, pp. 13–22, 2015.https://doi.org/10.1002/asi.23201
27
H. Lütkepohl and M. Krätzig,Applied Time Series Econometrics. Cambridge, UK: Cambridge University Press, 2004.
28

S. N. Soroka, Issue attributes and agenda-setting by media, the public, and policymakers in Canada, International Journal of Public Opinion Research, vol. 14, no. 3, pp. 264–285, 2002.

29

C. W. J. Granger, Investigating causal relations by econometric models and cross-spectral methods, Econometrica:Journal of the Econometric Society, vol. 37, no. 4, pp. 424–438, 1969.

30
J. D. Hamilton, Time Series Analysis. Princeton, NJ, USA: Princeton University Press, 2020.
31
W. Enders, Applied Econometric Time Series. Hoboken, NJ, USA: John Wiley & Sons, 2008.
International Journal of Crowd Science
Pages 53-62
Cite this article:
Liu J, Wang Y, He S, et al. A Quantitative Analysis of the Relationship Between the Public and News Media Attentions to Hot Network Events in China. International Journal of Crowd Science, 2022, 6(2): 53-62. https://doi.org/10.26599/IJCS.2022.9100011

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Received: 19 September 2021
Revised: 31 March 2022
Accepted: 06 April 2022
Published: 30 June 2022
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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