Postdoctoral Researcher in ERC project “The Implications of Selective Information Sampling fo

The research project “The Implications of Selective Information Sampling for Individual and Collective Judgments” (InfoSampCollectJgmt) funded by the European Research Council (ERC) is recruiting two Postdoctoral researchers with PhDs in Behavioral Science, Judgment and Decision Making, Cognitive Psychology, Marketing, Computational Social Science, Data Science, Economics or related fields. The project will be located at the Department of Economics and Business of Universitat Pompeu Fabra (Barcelona). The positions are offered for two years, and can be extended to three, starting between October and December 2018. The post-doctoral researchers will work with Prof. Gaël Le Mens.


Project summary (informal):

The polarization of attitudes across social groups is at the root of crucial challenges faced by our societies such as the rise of nationalism or populist ideologies. With his newly-awarded ERC Consolidator Grant, Prof. Gaël Le Mens, from Pompeu Fabra University, will study the mechanisms leading to such attitude polarization.

Prof. Le Mens’ project will combine insights from psychology, sociology and economics to understand how the way we select information shapes beliefs and attitudes. This project is timely, because social media are quickly transforming how people access information. Social media are making it easier for people to be exposed to news sources that agree with their opinions. And they can easily avoid information that questions or goes against their views. Prof. Le Mens will try to explain how these patterns of information consumption facilitated by social media affect individual and collective attitudes. His results will help understand phenomena that range from the impact of fake news to the persistence of negative stereotypes toward social groups that are different from our owns.


Academic Summary:

Much research has shown that judgments are the products of imperfect information processing heuristics. Recently, an alternative theoretical perspective has been proposed. It emphasizes that people form judgments by observing information samples about the alternatives. Sampling-based theories can explain numerous judgment patterns such as risk aversion, overconfidence, illusory correlations, the in-group out-group bias, or social influence.

The sampling approach has illustrated how these and other important patterns of human judgments can be parsimoniously explained by assuming a common source of bias. But at least two important questions remain:

  1. How do sampling explanations for judgment biases can be integrated with explanations that focus on information-processing biases in order to explain judgment patterns in naturally occurring environments?
  2. What are the implications of selective information sampling for collective judgments and the distribution of beliefs and attitudes over social networks?

I set to answer these pressing questions by (1) developing integrative belief formation models that incorporate both sampling-based mechanisms and information processing-based mechanisms; (2) collecting and analyzing experimental and field data to test these integrative models and uncover how the two classes of mechanisms interact; (3) building on these insights to develop models that lead to testable predictions about collective judgments and test these predictions with field and experimental data; (4) running experiments to measure the extent to which social network driven information sampling can contribute to opinion polarization.

The project will carry novel prescriptions to limit judgment biases such as the prevalence of negative stereotypes about socially distant others or the resistance to institutional change. It will also carry prescriptions to limit the emergence of collective illusions, and contain the polarization of opinions across social groups.