The talk will draw on Dr. King-wa Fu’s decade long experience in researching social media in China and Hong Kong, including China’s Internet censorship research: Weiboscope, WeChatscope, and more recently on Zhihu; and Hong Kong’s social movement mobilization on Telegram Channels. Dr. King-wa Fu will outline not only his lessons learned in these projects when collecting and analyzing data, but also put forward the opportunity for future study.
The biggest challenge in empirical work is to get our statistical models to correctly represent the politics of what we are studying. For example, Donald Trump raised voter turnout. So did Franklin Roosevelt and Adolf Hitler. Strong preferences motivate voters to go to the polls. Yet studies of elections nearly always analyze vote choices and turnout separately, missing the politics that mobilizes voters. Researchers have long understood the theoretical limitation of doing so, but issues of parameter identification, computing power, unavailability of survey weighting, and complexity of Read More
This talk introduces the theoretical and applied foundations of Bayesian statistical analysis in a manner appropriate to social and behavioral scientists The Bayesian paradigm is ideally suited to the type of data analysis required in these fields because it recognizes the mobility of population parameters, ncorporates prior knowledge that researchers possess, and updates estimates as new data are observed. Examples will be drawn from political science, public policy, and anthropology. Issues in Bayesian computing will also be discussed.
What do proportions of government budgets allocated to particular policy areas, support for political parties, and shares of total income for quartiles of a national population have in common? They are examples of compositional variables that evolve in important ways over time. In each case, we can express the outcome of interest as a set of relative proportions such that a gain in one area must be offset by a loss in another area or areas. In the Dynamic Pie Project, we are developing modeling strategies to allow researchers to test theories about the determinants of compositions as they Read More
NCHU Announcement 中興大學公告 Research shows that new information about the likely future policy direction of government can affect financial markets. So too can unexpected events, such as armed conflict or terrorist attacks. We build on existing research in two ways. First, we contend that news about a government’s resolve to follow through with their stated policies should also affect financial markets. We test this argument using data on President Donald Trump’s Mexico-related policy tweets both before and after he became president, finding that exchange rate volatility increases in response !--> Read More
NCHU Announcement 中興大學公告 Recently, Pfizer pharmaceutical company announced promising results from late-stage trails of an RNA based vaccine designed to induce immunity against COVID-19. For many, this evoked thoughts of the “beginning of the end” of this unprecedented global public health crisis. However, even the best of vaccines will be useless if people are unwilling to submit to inoculations. Just as fast as Pfizer announced the results, “anti-vaxxers” began questioning the safety of this new type of vaccine, and recent news reports suggest at least 35% of the !--> Read More
NCHU Announcement 中興大學公告 Quantitative social science represents a field of study, in which we collect and analyze data to understand and solve problems in our society. In this talk, Professor Imai discusses two of his own ongoing research projects that illustrate how to use scientific evidence for the evaluation of public policies. One project is about the detection of gerrymandering in legislative redistricting. This study shows how to determine whether a proposed redistricting plan is an outlier in terms of partisan or racial fairness dimensions by simulating an ensemble of !--> Read More
NCHU Announcement 中興大學公告 In forecasting US presidential elections, there are different scientific approaches. First, there are structural models of political scientists that offer theory-driven regression equations . However, the most popular approach involves poll watching, led by data journalists who mine vote intention surveys. . Finally, there are lesser known, but promising methods, such as citizen forecasting. In this presentation, we consider the well-known Political Economy Model, using it as a basis of comparison with The Economist Model, which relies mainly on voter intentions. !--> Read More
NCHU Announcement 中興大學公告 “The Political Impact of Economic Change” (with Katherine Cramer) uses data from a long-term panel study of people who graduated from high school in 1965 to examine how income mobility and escalating economic inequality have shaped Americans’ partisanship and policy preferences over the past half-century. Overall, this cohort became distinctly more conservative on a variety of economic and social issues and distinctly more Republican, especially during the period of “stagflation” from 1973 through 1982. These conservative shifts were strongly concentrated among !--> Read More
NCHU Announcement 中興大學公告 How can we measure voter transitions between elections? It is standard to talk only about conversion and mobilization, but demobilization–voter dropout–also matters. Unfortunately, all three measures of electoral change are customarily computed with different denominators, making it impossible to compare their relative magnitudes. In this paper, we show how to compute these quantities comparably so that they add to the total vote change. Then we apply these ideas to the 2016, “Blue Wall” states—Wisconsin, Michigan, and Pennsylvania—which voted !--> Read More