The Oxford Handbook of Behavioral Political Science
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Research since the 1990s reveals that openness to experience—a personality trait that captures interest in novelty, creativity, unconventionalism, and open-mindedness—correlates negatively with political conservatism. This chapter summarizes this vast literature by meta-analyzing 232 unique samples (N = 575,691) that examine the relationship between the Big Five personality traits and conservatism. The results reveal that the negative relationship between openness to experience and conservatism (r = −.145) is nearly twice as big as the next strongest correlation between personality and ideology (namely, conscientiousness and conservatism; r = .076). The associations between personality traits and conservatism were, however, substantively larger in Western, educated, industrialized, rich, and democratic (WEIRD) countries than in non-WEIRD countries. The chapter concludes by reviewing recent longitudinal work demonstrating that openness to experience and conservatism are non-causally related. Collectively, the chapter shows that openness to experience is by far the strongest (negative) correlate of conservatism but that there is little evidence that this association is causal.

Forecasting political events is a critical activity for social scientists. Forecasting can help test competing theories, let researchers grapple with the true substantive effects of their models, and bridge the gap between academia and the policy world. Forecasting is an academic activity with direct relevance for policymakers. Yet, a variety of cognitive biases can make forecasting challenging, even for experts. Despite these limitations, interest in forecasting is growing. This chapter describes several different approaches to forecasting political events, especially international political events. These methods include game theory, machine learning, statistical analysis, and event data algorithms. Recent research also suggests the way models drawing on the wisdom of the crowds, forecasting teams, and prediction markets can generate large improvements in accuracy when forecasting geopolitical events. All have strengths and weaknesses, given the inherent uncertainty that exists in the political world.

Metaphors and analogies are two of the most popular heuristics utilized by decision makers, promoting an unconscious inference into the realm of rationality within the mind. A master of metaphor and analogy, the late leader of the People’s Republic of China (PRC), Mao Zedong, offers an illuminating example of such heuristic reasoning. Analyzing the metaphors and analogies most frequently invoked by the PRC leader, this chapter demonstrates that Mao’s conceptual system was highly metaphorical. While historical analogies explain Mao’s heuristic reasoning for China’s revolutionary diplomacy, his use of metaphors reveals how stereotypes influenced his understanding of his enemies, which in turn explained and shaped China’s major foreign policy decisions. Mao’s use/misuse of metaphors and analogies also showcases their fallacies, mainly their tendency to exaggerate similarities and move from the realization that something is like something else to assuming that something is exactly like something else.

Since the invention of Word2Vec by a Google team in 2013, natural language processing (NLP) techniques have been increasingly applied in the private sector, by government agencies across countries, and in the social sciences. This chapter explains NLP’s basic analytical procedure from preprocessing of raw text data to statistical modeling, reviews the most recent advances in NLP applications in political science, and proposes a new scaling approach for measuring political actors’ spatial preferences along with potential application in decision-making research. It argues that with a greater focus on explaining behavioral mechanisms and processes, which is a goal shared by artificial intelligence/computational modeling and cognitive science, NLP can help improve behavioral political science by its ability to integrate micro-, meso-, and macro-level analyses. Critical and reflexive use of NLP techniques, combined with big data, will lead to obtain better insights on political behavior in general.

In recent decades, political scientists have placed greater emphasis on research designs that are able to measure causal effects credibly. The discipline has also participated in a social science–wide trend toward greater reliance on psychological and sociological theories to explain behavior. Both of these trends have been readily integrated into voter mobilization field experiments. This chapter reviews studies that employ field experimental designs that test the implications of psychological theories about political participation. It also reviews the use of field experiments to test psychological theories originally developed to explain behaviors outside of voting and applied and tested in the context of voting through mobilization messages. Finally, the chapter reflects on the limitations and future directions of behavioral political science as it relates to voter mobilization field experiments and political participation.

This chapter reviews key themes and trends in the study of immigration attitudes in the political science literature spanning two decades. It begins with a data-driven examination of key trends in studies of attitudes toward immigration in top political science journals from 1996 to 2020, showing trends in terms of the quantity of studies, theoretical perspectives, empirical settings, and methodological approaches. The chapter then presents a narrative review of the literature, highlighting theoretical and methodological innovations as well as identifying gaps and pertinent questions to be addressed. It concludes by pointing to some promising directions for future research in the study of immigration attitudes.

A leader’s approach to foreign policy decision-making is a critical explanatory factor in understanding why certain decisions are made. While several tools are available to analysts who wish to examine the process by which decision makers settle upon their chosen alternative, one of the most compelling is applied decision analysis (ADA), which allows scholars to uncover the unique “decision DNA” associated with a given leader. This chapter surveys the literature that has used the ADA methodology to examine questions of foreign policy decision-making. It pulls from twenty studies of leaders’ decisions—with more than twenty different leaders, ranging from Winston Churchill to Mao Zedong to Osama bin Laden—which comprise more than one hundred total unique decisions, examining and discussing the findings of each. It draws inferences about which decision rules best explain leaders’ policy choices, concluding that the works in question show overwhelming support for the poliheuristic theory of decision; and it discusses how future scholars can build on the ADA research program and how this information can best be used by policymakers.

Although Herbert Simon and Allen Newell studied problem-solving by experts as well as nonexperts, political scientists generally understand “bounded rationality” to refer primarily to cognitive constraints: how we fall short of completely rational decision-making. This incomplete understanding deprives us of an enormously useful intellectual legacy, built not only by Newell and Simon but also by a wide array of cognitive scientists who have explored how humans have collectively solved very difficult problems such as eliminating smallpox or designing nuclear submarines. This chapter surveys this richer understanding of bounded rationality. Cognitive capacities receive as much attention as cognitive constraints. The chapter reports work on how cultural storehouses of knowledge and certain organizational arrangements amplify our cognitive capacities in both the short and the long run. Finally, it extracts from the literature a set of thematically related propositions that are building blocks for constructing macro-theories of politics out of cognitively realistic micro-premises.

Since at least 1964, public opinion scholars have searched for signs of “constraint” in the American public’s foreign policy attitudes. This chapter reviews these attempts and suggests that the ensuing work has ultimately fallen into two research traditions that have largely been conducted in isolation of one another: horizontal models that portray attitudes as being sorted along multiple dimensions on the same plane and vertical models that imply a hierarchical organization in which abstract values determine specific policy positions. It then offers a new—networked—paradigm for political attitudes in foreign affairs, leveraging tools from network analysis to show that both camps make unrealistically strict assumptions about the directionality and uniformity of attitude structure. The chapter shows that specific policy attitudes play more central roles than existing theories give them credit for and that the topology of attitude networks varies substantially with individual characteristics like political sophistication.

Political scientists have traditionally approached international negotiations from a rational perspective, focusing on states as unitary actors driven by cost–benefit considerations. In this literature, the element of passing time is largely treated within the contexts of changing circumstances, discounting utility, and learning processes under conditions of incomplete information. More recent research, drawing on a behavioral political science approach, has brought attention to additional factors, such as the influence of previous decisions made by actors on their mind-sets and, consequently, on their subsequent negotiation decisions. Two behavioral effects, which focus on this impact that have successfully been integrated into the international negotiations literature, are the sunk cost effect and more recently, inaction inertia. Whereas sunk costs lead decision-makers to stick to sub-optimal conflict policies, inaction inertia drives them to continue rejecting settlement opportunities after an attractive opportunity has been forgone. Both phenomena carry important implications for ongoing negotiation processes and provide explanations for negotiation failures that are not captured by classic rational models of negotiation. This chapter discusses the concept of time in negotiations as it is treated in the negotiation research and how behavioral political science has contributed to this body of knowledge by highlighting the influence of the shadow of the past on actors’ psychological states and negotiation decisions. The chapter expands on inaction inertia in negotiations, which has more recently been introduced into the literature, presenting latest findings and methodological developments.