Heterogeneous Diffusion of Government Microblogs and Public Agenda Networks during Public Policy Communication in China
Abstract
:1. Introduction
- As far as we know, this is the first attempt to construct a research framework for the heterogeneous diffusion of public policy information on government microblogs. The proposed research framework can guide the public policy information diffusion on government microblogs, reduce the degree of heterogeneity between government microblogs and public attention to public policy, and contribute to policy implementation and shaping the image of democratic governments.
- This study combines issue importance measures from information entropy with the traditional degree centrality, i.e., FS and DS entropy, to comprehensively measure the differences between GMANs’ and PANs’ attention to different issues. Meanwhile, we integrate the classical agenda-setting research methods, i.e., QAP correlation and regression analysis, to comprehensively measure the heterogeneous diffusion phenomenon between government microblogs and the public from three dimensions: differences in issue attention, degree of agenda heterogeneity, and agenda causality.
- The network agenda-setting theory is extended to public policy information diffusion on government microblogs. Extending from a single temporal cross-section to a time series perspective, we analyze the agenda-leading relationship between GMANs and PANs.
2. Literature Review
2.1. Heterogeneous Diffusion of Policy Information
2.2. Three Levels of Agenda-Setting Theory
2.3. Public Policy Communication and NAS
2.4. Information Diffusion on Social Networks and NAS
3. Research Methodology and Procedure
3.1. Case Selection
3.2. Data Acquisition and Preprocessing
3.3. Topic Modeling
3.4. Co-Occurrence Matrix Analysis
3.5. Agenda Network Analysis
3.5.1. Agenda Network Visualization
3.5.2. Node Importance Analysis in DS and FS Entropy
3.6. Correlation and Regression Analysis of Agenda Networks
4. Results
4.1. GMANs and PANs Analysis
4.2. Correlation Analysis of GMANs and PANs
4.3. The Impact of GMANs on PANs
4.4. The Impact of the PANs on GMANs
5. Discussion
- Government microblogs focus on “policy information interpretation”, while the public’s understanding of policy information is biased. This phenomenon may be due to the rigid form of policy propaganda and lack of policy information interaction, which causes the gap between policy interpretation of government microblogs and public policy understanding. Thus, it affects the public’s cognition and evaluation of public policies and may generate negative emotions due to bias in understanding or conflicts of interest. Given the above problems, the following communication strategies can be adopted by government microblogs. First, policy information diffusion should be media-oriented, maximizing the government’s media communication resources. In addition to traditional texts and pictures, use videos, films, motion graphics, big data, virtual reality, games, hyperlinks, and other media forms as needed. Second, the government takes the initiative to set issues and make them trending topics. Furthermore, the government invites the public to participate in discussions and accepts “reverse invitations” to directly join the public-led online discussion, promoting the interaction of policy communication.
- Government microblogs fail to guide PANs effectively. Although both government microblogs and the public are concerned with data disclosure, government microblogs focus more on positive data information, such as the decline in the divorce rate and the number of withdrawn divorce applications after the implementation of the policy. They aim to clarify the effectiveness of the divorce cooling-off period policy by releasing positive information to improve the public’s recognition of the policy. However, the public is still skeptical about implementing the policy from the perspective of personal interests and believes that the implementation of the policy may decrease the marriage rate. Therefore, the government should reasonably guide the public to correctly perceive the policy through government microblogs and other media, effectively propaganda the significance of the policy implementation, and timely answer the public’s doubts about the policy. Specifically, the government should first set up a multi-framework to interpret the policy from the perspective of realizing the people’s livelihood interests, the residents’ quality of daily life improvement, etc., rather than a grand narrative. Second, the government should adopt popular discourse to realize policy intention. For instance, using novel headlines, Internet buzzwords, and emoticons adds vitality to policy discourse. The distance between the policy disseminator and the policy audience can be dissolved through the novel and friendly discourse. It is conducive to the public’s understanding and acceptance of the policy and helps ease the social emotions arising from differences in understanding or conflicts of interest.
- The “public opinion on policy” is the public’s greatest concern, but government microblog attention is relatively low. Moreover, government microblogs fail to listen to public opinions and capture public concerns in time, thus affecting the timely and effective adjustment of their policy information diffusion strategies. The keywords “oppose, compulsory, freedom of marriage” reflect the negative attitude of a part of the public towards implementing the divorce cooling-off period policy and their opposition to the policy. At the same time, implementing the policy changes the public perception of marriage. The keywords “marriage, caution, no marriage“ reflect that the public is more cautious about marriage due to the restrictions on divorce imposed by the policy, which may decrease the marriage rate in China. It is worth noting that there is a strong voice supporting the implementation of the premarital cooling-off period policy. The policy advocates premarital medical examinations and safeguards spouses’ right to premarital information. Therefore, the government should listen and respond promptly to the public’s voice and consider gradually putting the “premarital cooling-off period” policy on the policy agenda. It will fundamentally help avoid impulsive divorce and reduce the divorce rate in China, thereby protecting marriage and family relations and maintaining social harmony and stability.
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Topics | Keywords | Government Microblog Posts (%) | Public Posts (%) |
---|---|---|---|
policy information interpretation | civil code, terms, content, legal literacy class, consent | 21.5 | 7.4 |
premarital cooling-off period | marriage, caution, marriage cooling-off period, suggest, no marriage | 1.5 | 6.4 |
litigious divorce | court, lawsuit, mediate, divorce, dispute | 11.5 | 2.2 |
public opinion on policy | vote, topics, oppose, compulsory, freedom of marriage | 8.5 | 53.2 |
withdrawal of divorce registration application | couples, divorce cooling-off period, withdrawal, marriage registration | 13.8 | 2.2 |
data information | divorce rate, marriage rate, decrease, data, inaccurate | 28.5 | 16.3 |
marriage and family counseling | Premarital education, counseling courses, marriage, family | 3.1 | 1.4 |
domestic violence and cheating | domestic violence, situations, women, protection, cheating | 10.8 | 9.2 |
child parenting in the family | divorce, minor children, parenting, children, marriage, breakdown | 0.8 | 1.7 |
A | B | C | D | E | F | G | H | I | |
---|---|---|---|---|---|---|---|---|---|
A | 2 | 8 | 15 | 2 | 16 | 0 | 2 | 0 | |
B | 2 | 0 | 40 | 0 | 13 | 0 | 5 | 1 | |
C | 8 | 0 | 7 | 0 | 5 | 0 | 3 | 1 | |
D | 15 | 40 | 7 | 1 | 142 | 1 | 46 | 2 | |
E | 2 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | |
F | 16 | 13 | 5 | 142 | 2 | 0 | 24 | 0 | |
G | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | |
H | 2 | 5 | 3 | 46 | 0 | 24 | 1 | 1 | |
I | 0 | 1 | 1 | 2 | 0 | 0 | 0 | 1 |
Issues in GMANs | The Importance of Each Issue in DS and FS Entropy | |
---|---|---|
DS Entropy | FS Entropy | |
A | 0.213 | 0.213 |
B | 0.026 | 0.038 |
C | 0.151 | 0.111 |
D | 0.056 | 0.058 |
E | 0.098 | 0.077 |
F | 0.203 | 0.243 |
G | 0.060 | 0.082 |
H | 0.169 | 0.141 |
I | 0.024 | 0.038 |
Issues in PANs | The Importance of Each Issue in DS and FS Entropy | |
---|---|---|
DS Entropy | FS Entropy | |
A | 0.127 | 0.138 |
B | 0.081 | 0.062 |
C | 0.039 | 0.047 |
D | 0.350 | 0.384 |
E | 0.039 | 0.037 |
F | 0.228 | 0.205 |
G | 0.005 | 0.006 |
H | 0.121 | 0.103 |
I | 0.011 | 0.018 |
Time Interval | QAP Correlation (Pearson’s r) |
---|---|
January | 0.57 * |
February | 0.50 ** |
March | 0.15 |
April | 0.06 |
May | −0.03 |
PANs | |||||
---|---|---|---|---|---|
January | February | March | April | May | |
GMANs t−1 | 0.538 * | 0.623 *** | −0.074 | −0.058 | |
Adjusted R-squared | 29.0% | 38.8% | 0.5% | 0.3% |
PANs | |||||
---|---|---|---|---|---|
January | February | March | April | May | |
PANs t−1 | 0.856 *** | 0.783 *** | 0.872 *** | 0.855 *** | |
Adjusted R-squared | 73.3% | 61.4% | 76.0% | 73.0% |
GMANs | |||||
---|---|---|---|---|---|
January | February | March | April | May | |
PANs t−1 | 0.24 | −0.04 | 0.33 | −0.03 | |
GMANs t−1 | 0.263 | 0.373 * | 0.505 * | 0.411 * | |
Adjusted R-squared | 6.9% | 13.9% | 25.5% | 19.1% |
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Cai, M.; Gong, X.; Liu, J. Heterogeneous Diffusion of Government Microblogs and Public Agenda Networks during Public Policy Communication in China. Entropy 2023, 25, 640. https://doi.org/10.3390/e25040640
Cai M, Gong X, Liu J. Heterogeneous Diffusion of Government Microblogs and Public Agenda Networks during Public Policy Communication in China. Entropy. 2023; 25(4):640. https://doi.org/10.3390/e25040640
Chicago/Turabian StyleCai, Meng, Xue Gong, and Jiaqi Liu. 2023. "Heterogeneous Diffusion of Government Microblogs and Public Agenda Networks during Public Policy Communication in China" Entropy 25, no. 4: 640. https://doi.org/10.3390/e25040640