Enhanced or distorted wisdom of crowds? An agent-based model of opinion formation under social influence

Abstract

We propose an agent-based model of collective opinion formation to study the wisdom of crowds under social influence. The opinion of an agent is a continuous positive value, denoting its subjective answer to a factual question. The wisdom of crowds states that the average of all opinions is close to the truth, i.e., the correct answer. But if agents have the chance to adjust their opinion in response to the opinions of others, this effect can be destroyed. Our model investigates this scenario by evaluating two competing effects: (1) agents tend to keep their own opinion (individual conviction), (2) they tend to adjust their opinion if they have information about the opinions of others (social influence). For the latter, two different regimes (full information vs. aggregated information) are compared. Our simulations show that social influence only in rare cases enhances the wisdom of crowds. Most often, we find that agents converge to a collective opinion that is even farther away from the true answer. Therefore, under social influence the wisdom of crowds can be systematically wrong.

Neuroeconomic Decisions in Cocoa Producers: Impact of Cooperative Innovation Methodology on Prospecting for Fair Trade Organic Niche as an Incentive for Agricultural Sustainability

“…It is possible that one of the reasons that many agri-food cooperatives in North America according to Cook and in South Africa under Ortmann and King [2,3] and other parts of the world present a cycle of parable responding to the external context and internal degeneration that they face as a result of their members' collective decisions would be influenced by a process of social influence in the crowds following a consensus and that the decisions of the majority would not always be the best and would reduce the collective error raised by Mavrodiev and Schweitzer, [59]. The context in which collective decisions would be made would depend on the initial situation from which the initial parameter would start (Size of the collective error in which the decision is made).…”

“…This false perception in the producer would increase the collective error of the collective decision by deciding to pay the same price for conventional cocoa beans (Table 2) and organic cocoa beans (Table 3) as per Mavrodiev and Schweitzer [59].…”

Neuroeconomics in Cooperatives: Hierarchy of Emotional Patterns in the Collective Decision-Making Process for Sustainable Development

“…To predict organizational behavior, it is sufficient to identify the learning process in a hierarchical path from the bottom up with the correlation of holistic integrated innovation competencies of each small producer in each of its microworlds facing individual entrepreneurship decisions developing competencies that would then allow him to make collective decisions at the managerial level in an organization. According to Mavrodiev, P.; Schweitzer (2021) [68] collective wisdom could establish that the average of all opinions is closer to the truth, but groups would make decisions to maintain their initial decision if no more information is available, but if they had more information they could change their initial decision as small cocoa producers who preferred to maintain their status as individual entrepreneurs even when they did not achieve the expected results in Zúñiga (2021) [9].…”

Tehran Stock Exchange, Stocks Price Prediction, Using Wisdom of Crowd

“…Surowiecki argues that independence acts as a counterbalance to herding behavior (Eickhoff & Muntermann, 2016). In reality, preserving independent opinions is challenging (Mavrodiev & Schweitzer, 2021). Coordinating decisions is more accessible in a centralized group (Eickhoff & Muntermann, 2016).…”