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"Emotions and the Processes of Voter Decision Making"
by David Redlawsk
The history of voting research is primarily a history of cross sectional analyses supplemented by somewhat more comprehensive panel studies. With relatively few exceptions, voting studies have mined survey research data with an eye to determining the relative importance of issues, candidate traits, and partisanship. Debates have focused, for example, on whether or not voters understand issues (Campbell, Converse, Miller, and Stokes, 1960; Nie, Verba and Petrocik, 1976), how candidate traits have become more important in the process (Wattenberg, 1991), and whether partisanship represents a psychological attachment (Campbell, et al, 1960) or is better conceived of as a retrospective evaluation (Fiorina, 1981).
While scholars debated the rise and fall of issues, party, and candidate factors in the vote decision, another perspective was developing, significantly informed by psychological approaches to human behavior. This perspective sees voters as interacting with their political environment, rather than as vessels into which the environment flows. It recognizes that elections occur over time, that voters are exposed to information about candidates which they seek to put into perspective, but which changes as the campaign continues. This leads to a focus on how voters actually process the information they receive, how the contents and organization of political memory might affect the decision process, and the ways in which voters might keep track of the mass of information prevalent during a typical presidential campaign.
Even more recently, political psychologists interested in voter behavior have begun looking closely at the role emotions play in this decision process. Guided by work on affective intelligence by Marcus and his colleagues (Marcus and MacKuen, 1993; Marcus, Neuman, and MacKuen, 2000) and a somewhat competing motivated reasoning perspective from Taber and Lodge (2006), in my own work I have been attempting to understand how the emotional responses voters have towards information about candidates conditions their evaluations of that information and the integration of those individual evaluations into a global sense of which candidate best matches the voter’s preferences.
The fact is that both Marcus’s affective intelligence perspective and Lodge’s motivated reasoning approach work at the level of individual pieces of information – that is, they are both theories of what happens when a voter encounters new information, having already established some level of expectations from an existing information environment. Motivated reasoning argues that the affective (emotional) tag associated with existing knowledge structures interacts with the affective value of incoming information in a manner than may bias the evaluation of that new information. In short, if you like a candidate and you learn something potentially bad about that candidate, you may end up liking her even more, as you (mentally) counter-argue, discount, or otherwise devalue the new incongruent information. Thus voters may be motivated to maintain an existing positive evaluation even in the face of countervailing information. This would, of course, not really be “rational” in the sense of accurate updating of prior evaluations.
On the other hand, affective intelligence seems to argue that emotions – specifically anxiety – have the potential to enhance learning and thus, presumably, make citizens into better information processors. An affectively intelligent voter would be alerted to incongruency in the environment through the action of the surveillance system, which would put the voter on alert, presumably to begin gathering more information about that which raised the alarm. Like motivated reasoning, this is about “bits” of information – that is, the surveillance system recognizes that a new bit of information is unexpected, incongruent with the environment.
Many interesting questions arise from either of these perspectives. Can motivated reasoners ignore reality forever – that is, can they continue to support an initially liked candidate even in the face of a great deal of negative information? And does motivated reasoning also work to maintain negative evaluations in the face of positive information? If anxiety motivates a voter to learn more, at what point does anxiety become counterproductive, result in an inability to effectively function, and perhaps then a disengagement from the election process? Are anxious voters actually more informed voters? These and other key questions form the base of the research agenda we are now pursuing using a technique we call “dynamic process tracing”.
Richard Lau and I have argued that the dynamics of voter decision making and the effects of emotional response on information processing cannot be studied effectively with static approaches, such as cross sectional survey research. Instead, what is necessary is a methodology designed to understand decision making as it occurs, as voters encounter, process, respond to, and evaluate information about the choices in any given election. Our dynamic process tracing methodology does just this with a computer-based system that presents lab subjects with an election campaign mimicking the essential features of all political campaigns, especially the fact that they inevitably unfold over time. (Lau, 1995; Lau and Redlawsk, 2001) As our voters learn about their choices in an election, we track each step they take, every piece of information they encounter, and each evaluation that they make. The resulting dataset provides us with a wealth of ways to examine voter decision making, information processing, and the role emotions can play. Our dynamic process tracing system is most fully set forth in our recent book How Voters Decide: Information Processing during Election Campaigns (2006) and space precludes detailing it any more here.
I have used dynamic process tracing to examine whether the basic tenets of motivated reasoning apply to voters (Redlawsk, 2002), finding that in fact when voters encounter new information that is counter expectations, they stop-and-think, processing more carefully perhaps, but not necessarily without bias. Indeed I find that voters do in fact become more positive about a liked candidate after learning a small amount of negative information. At the same time, while finding support for some motivated reasoning processes, other studies we have done (Redlawsk, Civettini, and Lau, forthcoming) show evidence that under certain conditions anxious voters actually do learn more about the candidates who make them anxious and become more accurate in placing those candidates on issues after the election is over. Are these contradictory? That is, can voters simultaneously become more careful processors, more knowledgeable about their choices, and yet be motivated to maintain an existing evaluation even when that evaluation is no longer supported by the facts? We’ve seen both processes happen in our studies.
One possibility is that there is in fact what we call an “affective tipping point”, a point at which even the strongest motivated reasoner recognizes reality and rather than continuing to strengthen a positive evaluation in the face of negative information, finally begins to update more accurately for the remainder of the campaign (Civettini and Redlawsk, 2005). Thus, we suggest that motivated reasoning may be the initial stage when unexpected (read negative) information about a liked candidate is encountered, but that as more such information accumulates, maintaining a positive evaluation becomes perhaps anxiety-provoking, leading to a reassessment and a readjustment. At the moment this last bit is more speculative than established, but it points out the true power of dynamic process tracing. Unless and until voter information processing is truly conceived of and modeled as a process, rather than some static thing, we cannot effectively account for how candidate evaluations are developed and updated and the role emotions have to play.
David P. Redlawsk is Associate Professor of Political Science at the University of Iowa, Iowa City.
REFERENCES
Campbell, Angus, Philip E.Converse, Warren E. Miller, and Donald Stokes. 1960. The American Voter. New York: John Wiley and Sons, Inc.
Civettini, Andrew, and David P. Redlawsk. 2005. A Feeling Person’s Game: Affect and Voter Information Processing and Learning in a Campaign. Paper presented at the Annual Meeting of the American Political Science Association, Washington, DC.
Fiorina, Morris P. 1981. Retrospective voting in American national elections. New Haven: Yale University Press.
Lau, Richard R. 1995. Information search during an election campaign: Introducing a process tracing methodology for political scientists.” In M. Lodge and K. McGraw (Eds.) Political judgment: Structure and Process (pp. 179-206). Ann Arbor, MI: University of Michigan Press.
Lau, Richard R., and Redlawsk, David P. 2001. An experimental study of information search, memory, and decision making during a political campaign. In J. Kuklinski (ed.), Political psychology and public opinion. New York: Cambridge University Press.
Lau, Richard R., and David P. Redlawsk. 2006. How Voters Decide: Information Processing during Election Campaigns. New York: Cambridge University Press.
Marcus, George E., and Michael MacKuen. 1993. Anxiety, enthusiasm, and the vote: The emotional underpinnings of learning and involvement during presidential campaigns. American Political Science Review 87(September): 672-685.
Marcus, George E., W. Russell Neuman, and Michael MacKuen. 2000. Affective Intelligence and Political Judgment. Chicago: University of Chicago Press.
Nie, Norman H., Sidney Verba, and John R. Petrocik. 1976. The Changing American Voter. Cambridge: Harvard University Press.
Redlawsk, David P. 2002. Hot cognition or cool consideration? Testing the effects of motivated reasoning on political decision making. Journal of Politics 64: 1021-1044.
Redlawsk, David P., Andrew Civettini, and Richard R. Lau. Forthcoming. Affective Intelligence and Voting Information Processing and Learning in a Campaign. In The Affect Effect: Dynamics of Emotion in Political Thinking and Behavior, eds. Ann Crigler, Michael MacKuen, George E. Marcus, and W. Russell Neuman. Chicago, IL: University of Chicago Press.
Taber, Charles S., and Milton Lodge. 2006. Motivated Skepticism in the Evaluation of Political Beliefs. American Journal of Political Science 50(3): 755-769.
Wattenberg, M. P. 1991. The rise of candidate-centered politics: presidential elections of the 1980s. Cambridge, MA: Harvard University Press.
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