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Statistics Colloquium by Madeleine Boutet ’20

Wed, February 12th, 2020
1:10 pm
- 1:50 pm

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A Network Approach to Analyzing Information Gerrymandering and Undemocratic Decision Making by Madeleine Boutet ’20, Statistics Colloquium, Wednesday, February 12, 1:10 – 1:50 pm, Stetson Court Classroom 105

Abstract:  Over the past decade, distorted and false information has disrupted political discourse and threatened democratic decision making.  One approach to studying this threat has been the development of scientific methods to understand how networks that constrain the flow of information influence group decision making.  Stewart et al. (2019) developed a voter game as a model system to study information flow in competing decisions.  By using methods of network analysis, the authors uncovered a phenomenon they labeled ‘information gerrymandering’: the structure of the influence network can sway the vote outcome towards one party, even when both parties have equal sizes and each player has the same influence.  Simulations confirm that this phenomenon also exists in larger, more heterogeneous networks.  In this talk I will introduce the methods used to create and implement the voter game, mathematically define information gerrymandering, and discuss how different structures of information networks can constrain information flow and lead to undemocratic decision making. I  will end by examining real-world examples of influence networks and information gerrymandering.

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