Learning to be Biased

Ch'ng, Kean Siang and Zaharim, Norzarina (2009): Learning to be Biased.

Abstract

We simulate societal opinion dynamics when there is confirmation bias in information gathering and spread. If decision making is influenced by confirmation bias, the agent puts more weight on positive information to confirm hypothesis or reservation in the learning process, which renders selectivity in information gathering. If the utility discovered post purchase is low, it is externalized rather than internalized (i.e., self blame) for the selectivity of information. This causes the agent to outweigh the negative information. These two mechanisms are simulated to investigate the societal opinion dynamics and explain behavioral patterns such as overconfidence, stickiness of response and ``success breeds success" phenomenon.

• Item Type: MPRA Paper
• Language: English
• Keywords: Confirmation bias; Opinion percolation and convergence; Selectivity in information search; Hypothesis testing
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; D - Microeconomics > D0 - General > D01 - Microeconomic Behavior: Underlying Principles

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