We study learning and influence in a setting where agents communicate according to an arbitrary social network and naïvely update their beliefs by repeatedly taking weighted averages of their neighbors’ opinions. A focus is on conditions under which beliefs of all agents in large societies converge to the truth, despite their naïve updating. We show that this happens if and only if the influence of the most influential agent in the society is vanishing as the society grows. Using simple examples, we identify two main obstructions which can prevent this. By ruling out these obstructions, we provide general structural conditions on the social network that are sufficient for convergence to truth. In addition, we show how social influence changes when some agents redistribute their trust, and we provide a complete characterization of the social networks for which there is a convergence of beliefs. Finally, we survey some recent structural results on the speed of convergence and relate these to issues of segregation, polarization and propaganda.
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Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number
2007.64.
Find related papers by JEL classification: D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation Z13 - Other Special Topics - - Cultural Economics - - - Social Norms and Social Capital; Social Networks Economic Anthropology
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