Thursday, February 26, 2015

Does Internet Control Increase Support for Governments?



by Leah Liu

Internet is having a growing impact over politics. People complain and organize protest against governments online. Rival countries or political competitors discredit the ruling party by spreading rumors on social media. As a result, some governments set up national firewall and block websites that contain opinions against the ruling party. Countries with less Internet freedom argue that the control is necessary for social stability and national security. Monitoring information as a way to protect reputation and maintain popular support has long been practiced by political rulers. In the information age, however, does the approach still work? Even with the Great Firewall in China, people can still find ways to get around the walls and get information from the outside. Some of them use softwares built by companies or individuals promoting Internet freedom and with a single click, they are out in the free world.


This led me to think—wouldn’t controlling the Internet backfire for the governments? Since it is very difficult to completely isolate a country’s network from the outside, at least some people within the country will have access to denouncing opinions of their own government. Blocking those voices shows the government’s lack of confidence in itself as well as in its people. Wouldn’t people in return have less faith in their government? Or do they still genuinely support their leaders because the majority of the country are not exposed to unfavorable information of the government? To find out the answer, I conducted the research and evaluated the effect of Internet freedom on public opinion towards their governments by comparing data of 42 countries in the world. The findings could give us better insight of the rationality behind government censorship over the Internet and possible policy implications.

To measure the public opinion of the governments, I pulled the 2014 “Confidence in National Government” data from the World Poll Survey of Gallup Analytics. The company did the annual survey in over a hundred countries. For the scores of “Confidence in National Government”, they measure the percentage of respondents with a positive answer to the question “In this country, do you have confidence in the national government?” and make a ranking of all surveyed countries. For the level of Internet freedom, I used the Freedom On the Net scores from Freedom House. They rated 65 countries in 2014 through the examination of three categories: governmental efforts to block certain technologies; governmental efforts to limit certain contents; legal protection on Internet users’ rights. Higher score means greater restriction over the Internet. Freedom House has so far the most comprehensive data on Internet freedom, but the total number of the countries they surveyed was not ideal for a quantitative research. Also, cross-referencing to “Confidence in National Government” data eliminated some choices in countries, thus the 42 observations in our study.




Besides the dependent and independent variables, I also included three control variables: Internet accessibility, economic development and regime type. These variables may also have an effect on the popular support of governments, and by controlling them in the data analysis, we can have more accurate result on the relations between Internet freedom and popular support of governments. The accessibility of Internet is measured by the number of Internet users per 100 people. Different from the accessibility of Internet content, this serves as an indicator of government’s performance on providing infrastructure. Together with economic development, as measured in GDP per capita, Internet accessibility affects people’s satisfaction with their governments. The third control variable is regime type and the score of the variable ranges from +10 (full democracy) to -10 (full autocracy). Countries with a democratic government generally enjoy greater support and are less likely to impose restriction over Internet freedom.

Figure 1 shows the bivariate relationship between Internet freedom and confidence in government. As indicated by the graph, there is a positive correlation and the increase in Internet restriction score is associated with the increase in government support.

Table 1 shows us how much the independent variable and control variables determined people’s confidence in their governments. Model 1 presents the unconditional effects, and Model 3 presents conditional effects. Without taking into consideration of other variables, every 1 point increase in Internet restriction is associated with 0.005-unit increase in confidence in national governments. The result is statistically significant (p<0.01) which means that there is only 1% possibility that the observed relationship happened purely by chance. After conditioning the effect of Internet accessibility, economic development and regime type on popular support of the government, the effect of our independent variable decreases, though not significantly, to 0.004. The result is still statistically significant. It is also worth mentioning that an increase in democracy score is associated with a slight decrease in government support, though the result is not statistically significant.

The finding seems to support the rationality behind controlling the Internet. What may be the possible explanation? First, the distrust of government stems from all social aspects. Factors like uncertain economic development, endangered national security and corrupted government can all lead to decreasing confidence in the ruling party. These problems exist in every country. As Internet growing to become the major source of information, countries with little or no restriction over Internet have to deal with all the reports on social problems, while countries with monopolies over information simply eliminate any challenging or disapproving opinions. This of course does not mean that countries like United States have more social problems than countries like Russia, but people do tend to have greater support of their governments when exposed to less unfavorable news. The theory may also be supported by the negative relationship between democratic level and confidence in government.


Does the finding mean that governments with a need to increase people’s support should start monitoring the Internet? Maybe, if they are desperate. But controlling information flow is never the solution to the dissatisfaction and distrust of the government. Governments should accept the fact that information is spreading faster than ever with the help of Internet. Instead of trying to control it, they should have faster and more effective response to possible accusation spreading online and also learn to use the Internet to their own advantage in publicity.


Appendix





3 comments:

  1. The research question of this blog post is clear and concise. It is also quite an interesting premise. The author determines this is a “disappointing result” but it may not be. Just because the IV does not have an effect on the DV as expected does not mean nothing can be learned from this post. It can be argued that Internet freedom has no effect on Government confidence and thus can be an argument to dissuade governments from cracking down on internet access. If what they are doing has no effect, why do it? Plus, you could bring in the benefits of access to internet to back up this statement, for example, better innovation, increased economic activity (when you consider giant tech firms like Google having offices in a country or persons simply being able to connect with international buyers for their products). In terms of the World Poll Survey used to pull the confidence in government data, it should be clearer what year that is from. That way a reader can be sure that it is relevant to the internet freedom data of 2014. Also, the argument that Internet accessibility has an effect on government support is not altogether convincing. Perhaps there is a way to convert this to a dummy variable showing high access and low access to internet and then doing an interaction with the IV? To see if the level of accessibility may affect the results (Similarly to the problem set where we did high and low development using the median HDI). There is also no comment on reverse causality, this should be addressed.

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  2. Big Picture
    1. Clear research?
    Yes, the intro and the tables explain very well what you are trying to study and why. The scatter plot doesn’t show on the blog. You also did a good job in explaining your sample and your variables. Great job in explaining that although your sample is small, the quality of it and of the variables is good and justifies the analysis.
    IV: Internet Freedom
    DV: Confidence in Government
    2. Who cares? You did a good job in explaining the importance of the problem and why it is relevant in today’s world to study this problem. Maybe I would have included some data to situate us in the context.
    3. Answered the question? Yes, you did answer the question. Internet freedom is not a determinant of government confidence.

    Nuts and Bolts
    4. Bivariate graph: The bivariate graph doesn’t show in the post
    5. yes, both summary and regression table are in the post.
    6. Both tables look good but the graph doesn’t show.
    Modelling and inference
    7. Evidence of transformation as needed? Yes, the author tried to look for linearity and found it as explained by the text.
    8. Cofounds? The model control for cofounds really well. I would probably add education or political participation to the model.
    9. Reverse causality? You controlled for it by adding well-chosen control variables.
    10. Correct interpretation free of jargon? The interpretation is correct but I would have also said more about the other control variables that were not significant because they are findings as well. You use simple language so the general audience wouldn’t have had problems reading your post.

    Overall comments:
    The theme is really interesting and you did a great job in selecting your data base and your variables. I think you could further explain the results by incorporating the control variables although they were not significant. Your tables looked good and the only problem was that I couldn’t see the graph. Great job!

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  3. It's well organized with appropriate control variables. I;m thinking about the indicator for economic development, GDP per capita. I wonder if other indicators for development would have different effect.
    The study is relevant, and the explanations for why are good. I think it's valuable even though the results aren't what you predicted.Sample size and variable adjustments may yield something different, possibly. At least your analysis with these particular variables and sample meet the objective and answer the question.
    The graph is hidden but your tables show the right information. This is one of those really interesting projects that can be done using so many independent and control variables, especially as internet usage stats change over time. Your explanation makes this very clear and easy to follow.

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