An Experimental Study of Persuasion Bias and Social Influence in Networks

Date: 2015-05
By: Jordi Brandts
Ayça Ebru Giritligil
Roberto A. Weber
URL: http://d.repec.org/n?u=RePEc:bge:wpaper:829&r=net
In many areas of social life, individuals receive information about a particular issue of interest from multiple sources. When these sources are connected through a network, then proper aggregation of this information by an individual involves taking into account the structure of this network. The inability to aggregate properly may lead to various types of distortions. In our experiment, four agents all want to find out the value of a particular parameter unknown to all. Agents receive private signals about the parameter and can communicate their estimates of the parameter repeatedly through a network, the structure of which is known by all players. We present results from experiments with three different networks. We find that the information of agents who have more outgoing links in a network gets more weight in the information aggregation of the other agents than under optimal updating. Our results are consistent with the model of “persuasion bias” of DeMarzo et al. (2003).
Keywords: persuasion bias, experiments, bounded rationality
JEL: C92 D03 D83
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Boundedly Rational Opinion Dynamics in Directed Social Networks: Theory and Experimental Evidence

Date: 2014-01
By: Pietro Battiston
Luca Stanca
URL: http://d.repec.org/n?u=RePEc:mib:wpaper:267&r=net
This paper investigates opinion dynamics and social influence in directed communication networks. We study the properties of a generalized boundedly rational model of opinion formation in which individuals aggregate the information they receive by using weights that are a function of their neighbors’ indegree. We then present an experiment designed to test the predictions of the model. We find that both Bayesian updating and boundedly rational updating à la DeMarzo et al. (2003) are rejected by the data. Consistent with our theoretical predictions, the social influence of an agent is positively and significantly affected by the number of individuals she listens to. When forming their opinions, agents do take into account the structure of the communication network, although in a sub-optimal way.
Keywords: Social Networks, Learning, Social In uence, Bounded Rationality
JEL: D85 D83 A14 L14 Z13