The term “fake news” dominates social media feeds, and has entered our daily lexicon. Now, a team of researchers from six disciplines across the University of Illinois, and Stanford University plan to develop models and run empirical studies to understand how information, and misinformation is transmitted.
The project, “A Multimodal Approach to Network Information Dynamics,” will receive 6.25 million over five years.
The project builds on four major strands of Regenwetter's past work; 1) Political persuasion and panel survey data 2) Empirical work on consensus methods, 3) Models and methods to understand heterogeneity of behavior, and 4) Understanding the scope of behavioral theory.
“I expect all four of these areas of expertise to be hugely important to the MURI project. One of the first questions we want to tackle, as the MURI grant starts, is to study how participants in an experiment update beliefs based on exposure to true and false evidence. A core question here is whether it is reasonable to model human decision makers as people who intuitively follow the rules of probability theory (rational theory). There is lots of prior evidence that people don’t follow probability calculus in their reasoning. We will look at this topic in a way that takes the 4 perspectives above into account. We also plan to switch from mere evidence to incorporate true and fake evidence.”
Aside from Professor Regenwetter, the research team includes: Cedric Langbort, a Professor of Aerospace Engineering, and Tamer Basar from the Department of Electrical and Computer Engineering.
Langbort adds, “We’ll be looking at aspects in the intentional or unintentional propagation of false stories and the psychological and emotional motivation behind propagating stories that aren’t based on proven data, for example.”
The researchers from Stanford, rounding out the team, are: Matthew Gentzkow from the Dept. of Economics, Jeff Hancock from the Dept. of Communications and founder of the Stanford Social Media Lab, and Johan Ugander from the Dept. of Management Science and Engineering.
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