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Phase transition to a two-peak phase in an information-cascade voting experiment
Shintaro Mori1, Masato Hisakado, Taiki Takahashi
1Department of Physics, Kitasato University, Kitasato 1-15-1, Sagamihara, Kanagawa, Japan. mori@sci.kitasato-u.ac.jp
Observational learning can cause populations to choose suboptimal options. A study reveals a phase transition where too many herders halt information aggregation, leading to poor collective decisions.
Area of Science:
- Social Psychology
- Behavioral Economics
- Statistical Physics
Background:
- Observational learning is a key mechanism for information aggregation in populations.
- However, it can lead to collective suboptimal choices and information cascades.
- The conditions under which this occurs and if it represents a phase transition are not well understood.
Purpose of the Study:
- To investigate the conditions under which observational learning leads to suboptimal choices.
- To determine if the termination of information aggregation in large populations constitutes a phase transition.
- To establish a microscopic rule for herder behavior and its macroscopic consequences.
Main Methods:
- A voting experiment with approximately 50 subjects answering a two-choice quiz sequentially.
- Subjects had the option to observe and copy prior choices (herders).
- A large-scale simulation (10^6 subjects) of a stochastic model based on observed herder behavior.
Main Results:
- A microscopic rule for herder behavior was identified.
- Varying the ratio of herders significantly altered macroscopic behavior.
- Low herder ratios led to rapid convergence to correct choices; high ratios resulted in extremely slow convergence and near-total information aggregation failure.
- Simulations showed a phase transition to a 'two-peak phase' where convergence completely terminated above a critical herder ratio.
Conclusions:
- The ratio of individuals engaging in observational learning critically impacts collective decision-making.
- A high proportion of herders can induce a phase transition, halting effective information aggregation and leading to suboptimal outcomes.
- This provides a mechanism for understanding how social learning can fail in large populations.
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