Media guiding effects on public perceptions of the Chinese government anticorruption: evidence from a survey experiment

Available online at www.sciencedirect.com Available online at www.sciencedirect.com Available online at www.sciencedirect.com

ScienceDirect 00 (2017) Procedia Computer Science 122 (2017)000–000 447–454 Procedia Computer Science 00 (2017) 000–000

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

Information Technology and Quantitative Management (ITQM 2017) Information Technology and Quantitative Management (ITQM 2017) Media guiding effects on public perceptions of the Chinese government Media guiding effects on public perceptions of the Chinese government anticorruption: evidence from a survey experiment anticorruption: evidence from a survey experiment a

Meihong Zhua,*, Aihua Lib Meihong Zhua,*, Aihua Lib

Capital University of Economics and Business, Beijing, 100070,China CentralUniversity UniversityofofEconomics Finance and Beijng,100081,China Capital andEconomics, Business, Beijing, 100070,China

ab b

Abstract Abstract

Central University of Finance and Economics, Beijng,100081,China

In this paper, we examine the guiding effect of media coverage on public perceptions of government anticorruption We design a survey experiment in which the onlyperceptions experimental is the In this paper, inweChina. examine the guiding effect of mediaframe coverage on public of factor government information of in media coverage. Baseda on the SoJump online survey platform, divide respondents intoisthree anticorruption China. We design survey experiment frame in which thewe only experimental factor the treatment groups and acoverage. control group in each treatment group stimulated by one kind of information of media Basedwhere on therespondents SoJump online survey platform, we are divide respondents into three media coverage collect a valid sampleinofeach about 5700 respondents. The results of General treatment groups information. and a controlWe group where respondents treatment group are stimulated by one kind of Linear Model (GLM) analysis We indicate thata three experimental factor haveThe statistically significant media coverage information. collect validtreatments sample ofofabout 5700 respondents. results of General positive effects(GLM) on respondents’ perceptions of treatments governmentofanticorruption. Specifically, the groupsignificant who are Linear Model analysis indicate that three experimental factor have statistically asked read information aboutperceptions results or of achievements government Specifically, anticorruptionthegive the who highest positivetoeffects on respondents’ government of anticorruption. group are evaluation on government followed by the group who read informationgive about asked to read informationanticorruption, about results then or achievements of government anticorruption thedisclosed highest major corruption cases, andanticorruption, the group whothen read followed information the government anticorruption policies and evaluation on government by about the group who read information about disclosed measures give thecases, lowerand evaluation than firstinformation two groups, and the government control group without any policies information major corruption the group whotheread about anticorruption and stimulus we find statistically disturbing relevant measuresgive givethe thelowest lowerevaluation. evaluation Passingly, than the first two two groups, and the significant control group withoutvariables any information to media give coverage in our design. The degree we of find concern anticorruption significantly affects stimulus the lowest evaluation. Passingly, two about statistically significantcoverage disturbing variables relevant respondents’ evaluation. high degree of concern give high coverage evaluation. The information to media coverage in ourRespondents design. The with degree of concern about anticorruption significantly affects channels or platforms from which respondents obtain anticorruption also has a significant effect respondents’ evaluation. Respondents with high degree of concerninformation, give high evaluation. The information on respondents’ evaluation. acquiring anticorruption information fromalso official give highest channels or platforms from Respondents which respondents obtain anticorruption information, has media a significant effect evaluation, and evaluation. respondentsRespondents getting information unofficial information media givefrom ranked-second evaluation, and on respondents’ acquiringfrom anticorruption official media give highest those who never get any anticorruption information any platform giveranked-second the worst evaluation. evaluation, and respondents getting information from from unofficial media give evaluation,These and conclusions will help authority to properly manage media platforms, give full play to the those who never get management any anticorruption information from any platform give the and worst evaluation. These positive roleswill of media’s in guiding public perceptions of government anticorruption. conclusions help management authority to properly manage media platforms, and give full play to the positive roles of media’s in guiding public perceptions of government anticorruption.

© © 2017 2017 The The Authors. Authors. Published Published by by Elsevier Elsevier B.V. B.V. Peer-review under responsibility of the scientific committee of the 5th International Conference on Information Technology Selection and/or peer-review under responsibility of the organizers of ITQM 2017 © 2017 The Authors. Published by Elsevier and Quantitative Management, ITQM 2017. B.V. Keywords: media coverage; perception; anticorruption;of survey experiment;oftreatment; effect;China Selection and/or peer-review under responsibility the organizers ITQM 2017 Keywords: media coverage; perception; anticorruption; survey experiment; treatment; effect;China

*

Corresponding author. Tel: 86-10-83952180. * E-mail address: [email protected]. Corresponding author. Tel: 86-10-83952180. E-mail address: [email protected].

1877-0509 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 5th International Conference on Information Technology and Quantitative Management, ITQM 2017. 10.1016/j.procs.2017.11.392

448

Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454 Meihong Zhu, Aihua Li / Procedia Computer Science 00 (2017) 000–000

1. Introduction For the Chinese Communist Party (CCP) and its government, anticorruption is related to the fate and future of the Chinese nation. Since 2013, the CCP and its government have extensively carried out the anticorruption battle and have made remarkable achievements. In the real world, many corruption behaviours are covert and the actual corruption degree of a country or a political party is difficult to measure. So, the corruption or incorrupt situation is usually evaluated by public subjective perceptions. In addition, anticorruption means more than simply prevention and punishment of corruption by the CCP and its government. Rather, it needs public understanding and willingness to participate in the battle. So, understanding the public perceptions and aspirations for anticorruption are crucial to the CCP and its government. Public perceptions of the government anticorruption are affected by personal factors and social factors. Zhu, Lu and Shi (2013) examined the effect of media channels on Chinese public perceptions of official corruption by using survey data in 2002. They concluded that, people who get information from formal sources shape more positive perceptions, while those getting information from informal sources such as rumors usually generate negative perceptions. Li, Gong and Xiao (2016) examined the perceptions of Chinese citizens towards government’s anticorruption through a survey of 1,604 Shanghai residents in 2008. They drew a conclusion that, two personal factors, including personal perceptions of unfairness in income distribution and intrusion of political power into economic affairs, affect respondents’ assessments on government anticorruption. In this paper, we try to explore the effect of the information (or contents) of media coverage on public perceptions of government anticorruption. Firstly, we develop hypotheses on the possible media coverage effect on public perceptions of government anticorruption. Secondly, we design a survey experiment frame to test these hypotheses. In all waves of survey experiments, the only common factor we concern about is the contents of media coverage of government anticorruption. We design three levels or treatments for the factor: (1) anticorruption policies and measures, (2) uncovered conspicuous corruption cases, and (3) anticorruption achievements or results. All waves of the survey experiment process are embedded into the SoJump online survey platform. In each wave of survey experiment, respondents are randomly allocated 4 groups in which the respondents in the first three groups are respectively stimulated by the above three levels of media coverage information and the respondents in control group are not given any information stimulation. Before filling in questionnaires, respondents in the first three groups are asked to read the media coverage information about government anticorruption. Rather, the respondents in control group can directly fill in questionnaires. In our research, approximately 5700 records of respondents are collected in the period of Xi jinping holding power. Then, we use General Linear Models (GLM) to test these hypotheses and to estimate the effect of the contents of media coverage on public perceptions of government anticorruption.Our analysis reveals that, respondents' perceptions of government anticorruption are very elastic to the contents of media coverage. Respondents in the three treatment groups give higher evaluation on government anticorruption than those in control groups. In order to reveal the influence of the media report more accurately, the individuals’ concerns about anticorruption topic and demographic characteristics and are also taken into account. Compared with the research of Zhu, Lu and Shi (2013), we also consider the influence of media information channels on public perceptions of government anticorruption, but we view information channel as the disturbing variable in analysis of the effect of the only factor(the contents of media coverage). 2.1 The characteristics of survey experiment Causal inference is always a very important research task, and so far, experiment design is still an effective tool for exploring it. In the field of social science, especially in that of public opinion research, small-scale causal relationship studies have been widely conducted in laboratories (Druckman, 2006; Gaines BJ, 2007). Since 1970s, with the rapid development of computer technology, computer-aided survey platforms have been designed. Researchers have been able to put complex experimental research into survey research platform, and then two kinds of researches are combined effectively, named as population-based survey experiments (Mutz,



Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454 Meihong Zhu, Aihua Li/ Procedia Computer Science 00 (2017) 000–000

449

2011) or survey experiments (Sniderman, 2011). In survey experiment, random assignment of respondents to treatment and control conditions enable to reveal whether one factor influences the target variable, while the availability of a representatively large sample from the survey platform can allow sample generalization to population. That is to say, survey experiments seem to maximize internal and external validity of casual inference. It provides a more advanced methodology to reliably evaluate casual relationships. Survey experiment is easy to implement, so it is widely used in social science, especially in public opinion research. 2.2. Setting of treatments In this research, we focus on whether the contents of the media coverage about the Chinese government anticorruption affect public’s perceptions or views about government anticorruption. So, in these series of survey experiments, the only common and controlled factor is the contents of media coverage of government anticorruption. It includes three levels respectively named as in table 1. Considering the control group, there are 4 levels or treatments in all. Table 1. Treatments and data in each group treatments

treatment name: contents of media coverage

groups and data

treatment 1

anticorruption policies and measures

group 1: 1490

treatment 2

uncovered conspicuous corruption cases

group 2 :1139

treatment 3

anticorruption achievements or results

group 3: 1761

treatment 4

control group

group4 : 1298

2.3. Design of questionnaires The survey experiments are carried out in 9 separate waves from June 2014 to March 2017. All waves have a common structure including 4 modules. Module A involves questions about that whether respondents concern of government anticorruption and where they get the anticorruption information. Module B includes 3 treatments providing information about government anticorruption solely for the three treatment groups. Module C describes 5 questions about respondents’ perceptions of government anticorruption. Module D lists socio-demographic background questions including age, gender, education, income, and occupation status. The order of modules for treatment groups is A, B, C and D, while that for control group is A, C and D. In each wave, 3 treatments and a control group are shown by 4 kinds of independent questionnaires. The core structure and questions of questionnaire are as follows. Module A: respondents’ concerns of government anticorruption A1. Do you concern of media coverage about the Chinese government anticorruption? Depending on the concern degree from low to high, a respondent is asked to select a number value from the ranking of 0 to 5. A2.Where do you get the information of media coverage about anticorruption (only for respondents whose concern degrees in A1 are more than 0)? 4 sources of information are provided for selection: domestic official media platform, domestic unofficial media platform, foreign media platform, and other media platform. Module B: treatments setting treatment 1: anticorruption policies and measures:7 important items are listed. treatment 2: uncovered conspicuous corruption cases: 7 important items are listed treatment 3: anticorruption achievements or results: 7 important items are listed Module C :Assessment items reflecting government anticorruption status

450

Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454 Meihong Zhu, Aihua Li / Procedia Computer Science 00 (2017) 000–000

C1. How well do you think of the government’s corruption prevention system? C2.How well do you think of the government’s corruption supervision system? C3. How well do you think of the government’s corruption punishment system? C4. How well do you think of the government’s overall anticorruption work? C5.How much belief do you have in the persistence, legalization and institutionalization of government's anticorruption battle in the next 5 to 10 years? For the above 5 items, 1-5 scale of scores are given for selecting where higher score indicates better evaluation on government anticorruption. Module D: information about respondents’ Demographic characteristics. It includes gender, age, education, occupation, and income. 2.4. Randomization of respondents and collection of data In each wave of survey experiment, based on the SoJump online survey platform, the respondents are randomly divided into 4 groups, and each group is given a version of the questionnaire. The questionnaires assigned to the first three groups have the identical structure as A+B1+C+D, A+B2+C+D, and A+B3+C+D, while the last group only includes module A, C and D. Data available for this research include 5688 records. Data distribution among groups is described in table 1. 3. Analysis 3.1. Hypotheses about effects In this paper, we focus on the analysis that whether the contents of media coverage will affect public’s perceptions and assessments of the Chinese government anticorruption status and what is the underlying influence mechanism. According to the analysis target, we make two hypotheses: (1) Different treatments generate different effects on respondents’ perceptions of government anticorruption. (2)The treatment effects for those who are exposed to media coverage are larger than for those who don’t receive any media information stimulus .To test the above hypotheses, we need to estimate the effect of each treatment of media coverage. 3.2. Models for effect estimation In survey experiment, randomization ensures that the respondents in each of the treatment groups are equivalent and thus the influence of confounding variables can be balanced. In general, when randomization is successfully achieved, the estimation of treatment net effects can be simply expressed as the experimental group’s assessment score minus that of the control group on a target variable (Imai K, 2008; Ron Kohavi, 2009; Kathryn M. Yount, 2013; Dingding Chen, 2015). But in this research, there are three treatment groups to be compared with control group, which belongs to the problem of multiple mean comparisons. If we compare one treatment group with control group each time, we need to conduct three times of this comparison. But the results of 3 times comparison are not stable. Even more unfortunately, since the randomization may not be fully followed in implement of survey experiment in social science literature, possibly interfering variables should be considered at the same time. In this case, the GLM analysis is appropriate. 3.3. Variables and measurements According to the questionnaire structure and content，all variables used for analysis are summarized in table 2.



Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454 Meihong Zhu, Aihua Li/ Procedia Computer Science 00 (2017) 000–000

451

Table 2. Variables and measurements

target variables

factor

possibly interfering variables

names Y1:assessment of government’s corruption prevention system Y2: assessment of government’s corruption supervision system Y3: assessment of government’s corruption punishment system Y4: assessment of government’s overall anticorruption work Y5:belief in the persistence, legalization and institutionalization of anticorruption in the next 5 to 10 years Y6:average of Y1,Y2 and Y3 Y7:average of Y1,Y2, Y3, Y4 and Y5 F:contents of media coverage X1:degree of concerns about government anticorruption X2:wave of survey experiment X3:media platform getting anticorruption information X4:gender X5:age X6:education X7: occupation X8: income

measurements ordinal :1-5 ordinal :1-5 ordinal :1-5 ordinal :1-5 ordinal:1-5 scale scale nominal:treatmnt1-4 ordinal :0-5 ordinal :1-9 nominal:1-5 nominal:1,2 ordinal:1-6 ordinal:1-5 nominal:1-7 ordinal:1-8

3.4. Preliminary analysis of relationships among variables In order to accurately estimate the net effects of all treatments of the media factor on target variables, we first analyze the possible relationships between all independent variables and all target variables by using one-way analysis of variance (one –way ANOVA). Table 3 describes the possible relationships. It can be seen that, leaving out other variables, F and all Xs (except to X4 and X8) have significant relationships with all Ys. These all significant variables will be incorporated into each GLM model for each Y in sequent analysis. Table 3. Possible relationships between all independent variables and all dependent variables

F X1 X2 X3 X4 X5 X6 X7 X8

Y1 sig=0.000 sig=0.000 sig=0.000 sig=0.000 sig=0.489 sig=0.004 sig=0.012 sig=0.000 sig=0.150

Y2 sig=0.000 sig=0.000 sig=0.000 sig=0.039 sig=0.724 sig=0.048 sig=0.001 sig=0.039 sig=0.584

Y3 sig=0.000 sig=0.000 sig=0.000 sig=0.002 sig=0.226 sig=0.031 sig=0.447 sig=0.000 sig=0.483

Y4 sig=0.002 sig=0.000 sig=0.000 sig=0.000 sig=0.710 sig=0.001 sig=0.075 sig=0.002 sig=0.224

Y5 sig=0.000 sig=0.000 sig=0.000 sig=0.000 sig=0.438 sig=0.000 sig=0.024 sig=0.000 sig=0.000

Y6 sig=0.000 sig=0.000 sig=0.000 sig=0.000 sig=0.786 sig=0.006 sig=0.054 sig=0.000 sig=0.181

Y7 sig=0.000 sig=0.000 sig=0.000 sig=0.000 sig=0.834 sig=0.000 sig=0.030 sig=0.000 sig=0.147

3.5. Estimation of treatment effects Here, we build General Linear Models for each Y to eliminate the impacts of all possibly interfering variables and to clearly reveal the net effect of each treatment. Estimations of regression coefficients of 4 treatments in the factor F with respect to each Y are shown in table 4. Then the net effects of the first 3 treatments relative to treatment 4 are directly the coefficients of them. For example, the data in the second column of table 4 show that, under the circumstance of controlling all interfering variables, factor F has a statistically significant affect on Y1. Detailedly, compared with the respondents in control group, the

Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454 Meihong Zhu, Aihua Li / Procedia Computer Science 00 (2017) 000–000

452

respondents who are stimulated by treatment 1, give a higher evaluation by 0.157 points on the government's corruption prediction system; Similarly, the respondents who are stimulated by treatment 2 give a higher evaluation by 0.131 points and the respondents who are stimulated by treatment 3 give a higher evaluation by by 0.192 points. Table 4. The net effect of each treatment on each Y treatment

Y1

Y2

Y3

Y4

Y5

Y6

Y7

Significance of Factor F 1 2 3 4 order of effects

sig=0.02

sig=0.00

sig=0.00

sig=0.00

sig=0.00

sig=0.00

sig=0.00

.157 .131 .192 0 3124

.158 .244 .210 0 2314

.105 .226 .238 0 3214

.144 .196 .236 0 3214

.136 .183 .275 0 3214

0.143 0.203 0.216 0 3214

0.140 0.196 0.210 0 3214

From table 4, it is clearly seen that, for each target variable Y, the media factor F is a statistically significant factor. Compared with the control group, net effect of each treatment on each Y is positive, which means that respondents who accept any type of anticorruption information stimulus will have more positive perceptions of government anticorruption than those without receiving any information stimulus. However, different types of information stimuli produce different net effects. Almost for all target variables, the orders of the net effects are 3>2>1, that is to say, respondents who receive information about government anticorruption results give the highest evaluation on the government anticorruption, followed by the respondents who receive information about conspicuous corruption cases, and then the respondents who receive information about anticorruption policies and measures. 3.6. Estimation of other effects Tables 5-8 show that, among all possible confounding variables X1-X8, only X1, X2, X3 and X8 present constant and significant effects on all Ys. Detailedly, X1 has a significantly positive effect on each Y, which means that the respondents who highly concerned about anticorruption issues give high evaluation on the government anticorruption work. X2 has 9 values, which indicates that 9 waves of survey experiments are implemented according to the timeline. It also has a significantly positive effect on each Y , that is to say, the evaluation of respondents on anticorruption in recent years are better than that in past years. X3 represents media platforms or sources from which respondents get anticorruption information. It also has a significant effect on each Y. Compared with those who never concern of government corruption (X1=0), respondents who get anticorruption information from official media give highest evaluation on government anticorruption, and respondents who get information from unofficial media give ranked-second evaluation. In respect to occupation X7, students, employee of state owned or institutions, and the unemployed or retired give higher evaluation than others. In all GLMs, other demographic characteristics have almost negligible effects. Table 5. The effect of X1 on each Y Significance of X1 0

Y1 sig=0.00 -0.399

Y2 sig=0.00 -0.434

Y3 sig=0.00

Y4 sig=0.00

Y5 sig=0.00

Y6 sig=0.00

Y7 sig=0.00

-.364

-.424

-.386

-.397

-.384

1

-0.370

-0.349

-.403

-.395

-.323

-.372

-.341

2

-0.172

-0.146

-.182

-.207

-.192

-.159

-.182

-.146

-.069

-.106

.011 0 654321

.008 0 564321

-.014 0 654321

3

-0.133

-0.049

-.078

4

-0.077

0.040

5 order of effects

0 654321

0 564321

-.004 0 654312

-.103 -.018 0 654321

Meihong Zhu, Aihua Li/ Procedia Computer Science 00 (2017) 000–000



Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454

453

Table 6. The effect of X2 on each Y Significance of X2 1 2 3 4 5 6 7 8 9 order of effects

Y1 sig=0.00 .012 -.447 -.387 -.608 .036 .356 .267 .006 0 6,7,5,1,8,9,3,2,4

Y2 sig=0.00 _ -.489 -.287 -.328 .288 .040 .459 .079 0 7,5,6,9,8,3,4,2

Y3 sig=0.00 .271 -.261 .019 .011 .371 0.181 .403 .230 0 7,5,1,8,6,3,4,9,2

Y4 sig=0.00 .003 -.433 .218 -.063 .018 .020 .167 -.160 0 3,7,6,5,1,9,4,8,2

Y5 sig=0.00 -.294 -.612 -.373 -.311 -.170 .052 .383 -.051 0 7,6,9,8,5,1,4,3,2

Y6 sig=0.00 .128 -.526 -.376 -.260 .163 .190 .294 .055 0 7,6,5,1,8,9,4,3,2

Y7 sig=0.00 -.053 -.391 -.121 -.247 .050 .119 .263 -.057 0 7,6,5,9,8,1,3,4,2

Table 7. The effect of X3 on each Y Significance of Factor X3 1:official media 2 :unofficial media 3:foreign media 4:other 5: never concern about anticorruption (X1=0) order of effects

Y1 sig=0.000 0.512 0.340 0.279 0.321 0.000 12435

Y2 sig=0.000 0.186 0.065 -0.017 0.045 0.000 12453

Y3 sig=0.000 .359 .227 .144 .140 0.000 12345

Y4 sig=0.00 .371 .232 .163 .075 0.000 12345

Y5 sig=0.00 .339 .199 .103 -.001 0.000 12354

Y6 sig=0.00 .411 .265 .211 .194 0.000 12345

Y7 sig=0.00 .327 .190 .113 .058 0.000 12345

Table 8. The effect of X7 on each Y Significance of Factor X7 1: Employees of state owned or institutions 2: Employees of foreign, private and joint stock enterprise 3: self-employed 4: farmers 5: Unemployed or retired 6: students 7: others order of effects

Y1 sig=0.012 .031 -.079

Y2 sig=0.001 .050 -.116

Y3 sig=0.159 -

Y4 sig=0.015 .060 -.044

Y5 sig=0.011 .097 -.076

Y6 sig=0.019 .020 -.104

Y7 sig=0.002 .058 -.090

-.131 -.094 .012 .034 0 6,1,5,7,2,4,3

-.055 -.234 .000 .069 0 6,1,5,7,3,2,4

-

.004 -.196 .058 .089 0 6,1,5,3,7,2,4

.022 -.089 .168 .077 0 5,1,6,3,7,2,4

-.074 -.181 .006 .023 0 6,1,5,7,3,2,4

-.034 -.151 .068 .053 0 5,1,6,7,3,2,4

4. Conclusions According to our survey experiment design frame and general linear models, the contents of the media coverage have important and significant impacts on the evaluation. Any kind of stimulus we list in this research can have a positive effect on the respondents' evaluation. But different stimuli still produce distinctly different effects. Specifically, the group of respondents who have read the materials about the results or achievements of government anticorruption give the highest evaluation on the government anticorruption work, then followed by the group of respondents who have read information about publicly uncovered major corruption cases, and the group of respondents who are given information stimulus about the government anticorruption policies and measures give the lower than the first two groups, while the control group of respondents who do not accept any information give the lowest evaluation . It is as expected that, respondents’ concerns about anticorruption topic have also significantly affect on their judgments of government anticorruption. In addition, the type of information channels or platforms from which the respondents obtain anticorruption information, also has a significant effect on their evaluation. At this point, our conclusion is similar to that of Zhu (2013). These conclusions are of great significance to the government's propaganda strategies of anticorruption. At

454

Meihong Zhu et al. / Procedia Computer Science 122 (2017) 447–454 Meihong Zhu, Aihua Li / Procedia Computer Science 00 (2017) 000–000

present, the Chinese government anticorruption situation is still grim. The media management authority should understand people's attitude towards anticorruption and the guiding mechanism of media to the public in viewing the government anticorruption (Stockmann, D.,2011). This will help the media management authority to properly manage media platforms, and give full play to their positive roles in guiding the public. Acknowledgements This research has been partially supported by grants #14YJA910005, Humanities and Social Science Research Fund of Chinese Education Ministry; # SM201510038006, Social Science Programme Found of Beijing Education Commission. References [1] Zhu JN, Lu J, and Shi TJ. When grapevine news meets mass media: different information sources and popular perceptions of government corruption in Mainland China [J].Comparative Political Studies, 2013, Vol.46 (8):920-946. [2] Li H, Gong T, Xiao HY. The Perception of anti-corruption efficacy in China: an empirical analysis [J]. Social Indicators Research , 2016 , 125 (3) :885-903. [3] Druckman JN, Green DP，Kuklinski JH, et al.. The Growth and development of experimental research in political science [J]. American Political Science Review, 2006, 100(4): 627-635. [4] Gaines BJ, Kuklinski JH and Quirk PJ. The Logic of the survey experiment reexamined. Political Analysis, 2007, 15 (1):1-20. [5] Mutz D C. Population-based survey experiments [M]. Princeton: Princeton University Press, 2011. [6] Sniderman P M. The Logic and design of the survey experiment: An Autobiography of a Methodological Innovation [C] //Druckman J N, Green D P, Kuklinski J H, et al. Cambridge Handbook of Experimental Political Science. Cambridge: Cambridge University Press，2011:182-205. [7] Imai K, King G，Stuart E A. Misunderstandings between experimentalists and observationalists about causal inference [J]. Journal of the Royal Statistical Society: Series A ( Statistics in Society), 2008,171(2): 481-502. [8]Ron Kohavi , Roger Longbotham, Dan Sommerfield, and Randal M. Henne. Controlled experiments on the web: survey and practical guide [J]. Data Min Knowl Disc, 2009, 18:140–181. [9]Kathryn M. Yount, Nafisa Halim, etc.. A Survey experiment of women’s attitudes about intimate partner violence against women in rural Bangladesh [J]. Demography, 2013, 50:333–357. [10] Chen DD, Cheng CY and Urpelainen J. Support for renewable energy in China: a survey experiment with internet users [J]. Journal of Cleaner Production: 2015, 19:1-9. [11] Stockmann, D., & Gallagher, M. Remote control: How the media sustain authoritarian rule in China. Comparative Political Studies, 2011, 44(4):436-467. [12] Li L, Lien D, Wu YP, Zhao Y. Enforcement and political power in anticorruption—evidence from China [J]. World Development, 2017, 98(10):133-147. [13] Melgar N, Rossi M, Smith T W. The Perception of corruption [J]. Internal Journal of Public Opinion Research, 2010, 22 (1): 120131.