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Modern Applied Statistics With S

Originally published in Contemporary Psychology: APA Review of Books, 1994, Vol 39(2), 225. Reviews the book, The Nature and Origins of Mass Opinion by John Zaller (1992). The author's commendable effort to specify a model of mass opinion formation offers readers an introduction to the prevailing vi

The Nature and Origins of Mass Opinion.

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

/pdf/text-as-data-the-promise-and-pitfalls-of-automatic-content-33q0hxlgsq.pdf

Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts

Thanks to the ready availability of political news today, informed citizens can protect and promote their own interests and the public interest more effectively. Or can they? Murray Edelman argues against this conventional interpretation of politics, one that takes for granted that we live in a world of facts and that people react rationally to the facts they know. In doing so, he explores in detail the ways in which the conspicuous aspects of the political scene are interpretations that systematically buttress established inequalities and interpretations already dominant political ideologies.

Constructing the Political Spectacle

Setting the Agenda: The Mass Media and Public Opinion

Social scientists have long hand-labeled texts to create datasets useful for studying topics from congressional policymaking to media reporting. Many social scientists have begun to incorporate machine learning into their toolkits. RTextTools was designed to make machine learning accessible by providing a start-to-ﬁnish product in less than 10 steps. After installing RTextTools, the initial step is to generate a document term matrix. Second, a container object is created, which holds all the objects needed for further analysis. Third, users can use up to nine algorithms to train their data. Fourth, the data are classiﬁed. Fifth, the classiﬁcation is summarized. Sixth, functions are available for performance evaluation. Seventh, ensemble agreement is conducted. Eighth, users can cross-validate their data. Finally, users write their data to a spreadsheet, allowing for further manual coding if required.

/pdf/rtexttools-a-supervised-learning-package-for-text-wljhvqpg5y.pdf

RTextTools: A Supervised Learning Package for Text Classification

Vote Switching in the 2016 Election: How Racial and Immigration Attitudes, Not Economics, Explain Shifts in White Voting

This article assesses the claim that sanctuary cities—defined as cities that expressly forbid city officials or police departments from inquiring into an individual’s immigration status—are associa...

https://journals.sagepub.com/doi/pdf/10.1177/1078087417704974

The Politics of Refuge: Sanctuary Cities, Crime, and Undocumented Immigration:

This article explores the effect of explicitly racial and inflammatory speech by political elites on mass citizens in a societal context where equality norms are widespread and generally heeded yet a subset of citizens nonetheless possesses deeply ingrained racial prejudices. The authors argue that such speech should have an ‘emboldening effect’ among the prejudiced, particularly where it is not clearly and strongly condemned by other elite political actors. To test this argument, the study focuses on the case of the Trump campaign for president in the United States, and utilizes a survey experiment embedded within an online panel study. The results demonstrate that in the absence of prejudiced elite speech, prejudiced citizens constrain the expression of their prejudice. However, in the presence of prejudiced elite speech – particularly when it is tacitly condoned by other elites – the study finds that the prejudiced are emboldened to both express and act upon their prejudices.

/pdf/the-trump-effect-an-experimental-investigation-of-the-akrnsoewz6.pdf

The Trump Effect: An Experimental Investigation of the Emboldening Effect of Racially Inflammatory Elite Communication

Public opinion research suggests that rapid and significant individual-level fluctuations in opinions toward various policies is fairly unexpected absent methodological artifacts. While this may generally be the case, some political actions can and do face tremendous backlash, potentially impacting public evaluations. Leveraging broadcast and newspaper transcripts as well as a unique two-wave panel study we demonstrate that a non-random, rapid shift in opinions occurred shortly after President Donald Trump signed executive order 13769 into law, which barred individuals from seven predominantly Muslim countries from entering the United States for 90 days. The ban set off a fury of protests across U.S. cities and airports, garnering tremendous media attention and discussion. Drawing insights from literature on priming, we claim that an influx of new information portraying the “Muslim Ban” at odds with inclusive elements of American identity prompted some citizens to shift their attitudes. Our study highlights the potential broad political effects of mass movements and protests as it pertains to policies that impact racialized minority groups, and suggests that preferences can shift quickly in response to changing political circumstances.

Loren Collingwood

Papers

RTextTools: A Supervised Learning Package for Text Classification

Vote Switching in the 2016 Election: How Racial and Immigration Attitudes, Not Economics, Explain Shifts in White Voting

The Politics of Refuge: Sanctuary Cities, Crime, and Undocumented Immigration:

The Trump Effect: An Experimental Investigation of the Emboldening Effect of Racially Inflammatory Elite Communication

A Change of Heart? Why Individual-Level Public Opinion Shifted Against Trump’s “Muslim Ban”