Dataset Information

How social influence can undermine the wisdom of crowd effect.

ABSTRACT: Social groups can be remarkably smart and knowledgeable when their averaged judgements are compared with the judgements of individuals. Already Galton [Galton F (1907) Nature 75:7] found evidence that the median estimate of a group can be more accurate than estimates of experts. This wisdom of crowd effect was recently supported by examples from stock markets, political elections, and quiz shows [Surowiecki J (2004) The Wisdom of Crowds]. In contrast, we demonstrate by experimental evidence (N = 144) that even mild social influence can undermine the wisdom of crowd effect in simple estimation tasks. In the experiment, subjects could reconsider their response to factual questions after having received average or full information of the responses of other subjects. We compare subjects' convergence of estimates and improvements in accuracy over five consecutive estimation periods with a control condition, in which no information about others' responses was provided. Although groups are initially "wise," knowledge about estimates of others narrows the diversity of opinions to such an extent that it undermines the wisdom of crowd effect in three different ways. The "social influence effect" diminishes the diversity of the crowd without improvements of its collective error. The "range reduction effect" moves the position of the truth to peripheral regions of the range of estimates so that the crowd becomes less reliable in providing expertise for external observers. The "confidence effect" boosts individuals' confidence after convergence of their estimates despite lack of improved accuracy. Examples of the revealed mechanism range from misled elites to the recent global financial crisis.

SUBMITTER: Lorenz J

PROVIDER: S-EPMC3107299 | biostudies-other | 2011 May

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

How social influence can undermine the wisdom of crowd effect.

Lorenz Jan J Rauhut Heiko H Schweitzer Frank F Helbing Dirk D

Proceedings of the National Academy of Sciences of the United States of America 20110516 22

Social groups can be remarkably smart and knowledgeable when their averaged judgements are compared with the judgements of individuals. Already Galton [Galton F (1907) Nature 75:7] found evidence that the median estimate of a group can be more accurate than estimates of experts. This wisdom of crowd effect was recently supported by examples from stock markets, political elections, and quiz shows [Surowiecki J (2004) The Wisdom of Crowds]. In contrast, we demonstrate by experimental evidence (N = ...[more]

PMID: 21576485

Similar Datasets

Project description:IntroductionTo mitigate the COVID-19 pandemic and prevent overwhelming the healthcare system, social-distancing policies such as school closure, stay-at-home orders, and indoor dining closure have been utilized worldwide. These policies function by reducing the rate of close contact within populations and result in decreased human mobility. Adherence to social distancing can substantially reduce disease spread. Thus, quantifying human mobility and social-distancing compliance, especially at high temporal resolution, can provide great insight into the impact of social distancing policies.MethodsWe used the movement of individuals around New York City (NYC), measured via traffic levels, as a proxy for human mobility and the impact of social-distancing policies (i.e., work from home policies, school closure, indoor dining closure etc.). By data mining Google traffic in real-time, and applying image processing, we derived high resolution time series of traffic in NYC. We used time series decomposition and generalized additive models to quantify changes in rush hour/non-rush hour, and weekday/weekend traffic, pre-pandemic and following the roll-out of multiple social distancing interventions.ResultsMobility decreased sharply on March 14, 2020 following declaration of the pandemic. However, levels began rebounding by approximately April 13, almost 2 months before stay-at-home orders were lifted, indicating premature increase in mobility, which we term social-distancing fatigue. We also observed large impacts on diurnal traffic congestion, such that the pre-pandemic bi-modal weekday congestion representing morning and evening rush hour was dramatically altered. By September, traffic congestion rebounded to approximately 75% of pre-pandemic levels.ConclusionUsing crowd-sourced traffic congestion data, we described changes in mobility in Manhattan, NYC, during the COVID-19 pandemic. These data can be used to inform human mobility changes during the current pandemic, in planning for responses to future pandemics, and in understanding the potential impact of large-scale traffic interventions such as congestion pricing policies.

Project description:Despite limited information and knowledge, we personally form beliefs about certain properties of objects encountered in our daily life-popularity of a newly released movie, for example. Since such beliefs are prone to error, we often revise our initial beliefs according to the beliefs of others to improve accuracy. Optimal revision requires modulating the degree of accepting others' beliefs based on various cues for accuracy-number of opinions, for example-such that the more accurate others' beliefs are, the more we accept them. Although previous studies have shown that such accuracy cues can influence the degree of acceptance during social revision, they primarily investigated problems with 'factually correct' answers, and rarely problems with 'socially correct' answers. Here we examined which accuracy cues are objectively useful (utility of cues), and how those cues are used (use of cues), in the social revision of people's beliefs about problems with 'socially correct' answers. We asked people to estimate the 'shared preferences (SPs)' for sociocultural items, the answers to which are determined by socially aggregated beliefs-how popular an abstract painting will be among a large crowd, for example-and then to revise their initial estimates after being exposed to other people's estimates about the same items. We considered 'confidence', 'agreement among estimates', and 'number of estimates' as accuracy cues. We found that, while all three cues validly signaled the accuracy of SP estimates, only the 'number' cue has a significant utility, but the other cues are much less useful for optimal revision. Nevertheless, people used the cues of 'agreement' and their own 'confidence' to the extent comparable to that of the 'number' cue. Our findings suggest that the utility and use of accuracy cues for problems with 'socially correct' answers differ from those with 'factually correct' answers, as follows: (i) confidence does not have a significant utility and (ii) but people use their own confidence while ignoring others' confidence.

Dataset Information

How social influence can undermine the wisdom of crowd effect.

Publications

How social influence can undermine the wisdom of crowd effect.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets