Abstract

The role of emotions in political behavior has been the subject of a substantial amount of recent research in political science. Perhaps the most well known argument about the role of emotions in shaping political behavior is Marcus, Neuman, and MacKuen's Affective Intelligence and Political Judgment (2000). Marcus and colleagues develop a theoretical perspective of the way that two basic emotions, anxiety and enthusiasm, drive attention to the political environment and shape political judgments. Anxiety, by alerting us to threat-ening stimuli in the environment, leads us to react to the environment by considering our options consciously and learn new information. Enthusiasm lets us know when our standing dispositions serve us well so that we can continue voting for whom we vote for, write checks to our regular interest groups and candidates, and basically leave politics out of our conscious considerations. Much of political behavior, however, seems not to be reactionary but action oriented. People desire something from government, set about a plan to secure that good or service, and (often relentlessly) execute that plan. Something other than anxiety must be causing this action-orientation. I argue that we must consider the role of hope in not only shaping political behavior but how politicians attempt to motivate citizens to vote, volunteer, and organize, among other civic activities. Political struggles are often about what is likely to happen rather than what has happened and this should cause us to consider how political behavior is prospectively oriented. Prospective emotions, or emotions about things that are expected to happen, likely hold the key to understanding political action more than current state emotions. Because hope concerns future goals and the plausibility of achieving those goals, it is an ideal candidate for understanding action oriented political behavior.KeywordsPositive EmotionGoal AttainmentPolitical BehaviorHigh HopeCollective GoalThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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