In almost every election cycle, the validity of the United States Electoral College is brought into question. The 2016 Presidential Election again brought up the issue of a candidate winning the popular vote but not winning the Electoral College, with Hillary Clinton receiving close to three million more votes than Donald Trump. However, did the popular vote actually determine the most liked candidate in the election? In this paper, we demonstrate that different voting policies can alter which candidate is elected. Additionally, we explore the trade-offs between each of these mechanisms. Finally, we introduce two novel mechanisms with the intent of electing the least polarizing candidate.
Significant research has been done by Stanford University scholars like Andy Hall, Shanto Iyengar, Bruce Cain, and David Brady, on polarization and election systems. Hall, Political Science Professor at Stanford, claims that "U.S. legislatures have become increasingly polarized and dysfunctional in part because of how difficult running for and holding office is." Combining theoretical and empirical evidence, he "shows how voters are forced to elect extremists because moderates don't run for office, and document[s] how the rising costs of running for office, and the falling benefits of holding office, have deterred moderates from running." @cite_1 Moreover, Hall has researched results in primaries @cite_14 , and concludes that extremists and their affiliated party tend to suffer penalties in the general election. To Hall, the general election system tends to have a moderating effect on elections in the House of Representatives in America. Similarly, Shanto Iyengar, another Political Science Professor, provides compelling evidence to support growing polarization in America. @cite_8 Iyengar's research raises important questions, many of which are beyond the scope of this paper.
@cite_14 @cite_1 @cite_8
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Political observers, campaign experts, and academics alike argue bitterly over whether it is more important for a party to capture ideologically moderate swing voters or to encourage turnout among hardcore partisans. The behavioral literature in American politics suggests that voters are not informed enough, and are too partisan, to be swing voters, while the institutional literature suggests that moderate candidates tend to perform better. We speak to this debate by examining the link between the ideology of congressional candidates and the turnout of their parties’ bases in US House races, 2006–2014. Combining a regression discontinuity design in close primary races with survey and administrative data on individual voter turnout, we find that extremist nominees—as measured by the mix of campaign contributions they receive—suffer electorally, largely because they decrease their party’s share of turnout in the general election, skewing the electorate towards their opponent’s party. The results help show how the behavioral and institutional literatures can be connected. For our sample of elections, turnout appears to be the dominant force in determining election outcomes, but it advantages ideologically moderate candidates because extremists appear to activate the opposing party’s base more than their own. This article studies the interplay of U.S. primary and general elections. I examine how the nomination of an extremist changes general-election outcomes and legislative behavior in the U.S. House, 1980 - 2010, using a regression discontinuity design in primary elections. When an extremist - as measured by primary-election campaign receipt patterns - wins a "coin-flip" election over a more moderate candidate, the party's general-election vote share decreases by approximately 9 -13 percentage points, and the probability that the party wins the seat decreases by 35 - 54 percentage points. This electoral penalty is so large that nominating the more extreme primary candidate causes the district's subsequent roll-call representation to reverse, becoming more liberal when an extreme Republican is nominated and more conservative when an extreme Democrat is nominated. Overall, the findings show how general-election voters act as a moderating filter in response to primary nominations. The American Voter - a seminal work in political science - uncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this paper, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media during the 2016 U.S. presidential primaries. Our analysis of 50 million tweets reveals the continuing importance of these three factors; our understanding is also enriched by the application of sentiment analysis techniques. The overwhelmingly negative sentiment of conversations surrounding 10 major presidential candidates reveals more "crosstalk" from Democratic leaning users towards Republican candidates, and less vice-versa. We uncover the lack of moderation as the most discussed personality dimension during this campaign season, as the political field becomes more extreme - Clinton and Rubio are perceived as moderate, while Trump, Sanders, and Cruz are not. While the most discussed issues are foreign policy and immigration, Republicans tweet more about abortion than Democrats who tweet more about gay rights than Republicans. Finally, we illustrate the importance of multifaceted political discourse analysis by applying regression to quantify the impact of party, personality, and policy on national polls. Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation. Language is the medium for politics and political conflict. Candidates debate and state policy positions during a campaign. Once elected, representatives write and debate legislation. After laws are passed, bureaucrats solicit comments before they issue regulations. Nations regularly negotiate and then sign peace treaties, with language that signals the motivations and relative power of the countries involved. News reports document the day-to-day affairs of international relations that provide a detailed picture of conflict and cooperation. Individual candidates and political parties articulate their views through party platforms and manifestos. Terrorist groups even reveal their preferences and goals through recruiting materials, magazines, and public statements. These examples, and many others throughout political science, show that to understand what politics is about we need to know what political actors are saying and writing. Recognizing that language is central to the study of politics is not new. To the contrary, scholars of politics have long recognized that much of politics is expressed in words. But scholars have struggled when using texts to make inferences about politics. The primary problem is volume: there are simply too many political texts. Rarely are scholars able to manually read all the texts in even moderately sized corpora. And hiring coders to manually read all documents is still very expensive. The result is that