Ever since Galton's classic demonstration of the wisdom of crowds in estimating the weight of a slaughtered ox, scholars of the mind and the public alike have been fascinated by the counterintuitive accuracy achieved by simply averaging a number of people's estimates. Surprisingly, individuals can, to some extent, harness the wisdom of crowds within the confines of their own mind by averaging s...

Although researchers have documented many instances of crowd wisdom, it is important to know whether some kinds of judgments may lead the crowd astray, whether crowds’ judgments improve with feedback over time, and whether crowds’ judgments can be improved by changing the way judgments are elicited. We investigated these questions in a sports gambling context (predictions against point spreads)...

We report on an experiment designed to explore whether allowing individuals to voice their anger prevents costly punishment. For this sake, we use an ultimatum minigame and distinguish two treatments: one in which responders can only accept or reject the offer, and the other in which they can also scold the proposer. By an unannounced successive two-person public goods game, with either the sam...

We propose a hierarchy of kinetic and macroscopic models for a system consisting of a large number of interacting pedestrians. The basic interaction rules are derived from [44] where the dangerousness level of an interaction with another pedestrian is measured in terms of the derivative of the bearing angle (angle between the walking direction and the line connecting the two subjects) and of th...

The illustrative videos FAST-xxx.mp4 and SLOW-xxx.mp4 illustrate fast and slow responses to complex systems to "business as usual" situations and unexpected stimuli, respectively. In the "business as usual" situation, nodes of key importance have the same initial reaction (marked by identical colors), which soon becomes the general response of the whole network. On the contrary, the initial res...

Collaborative filtering methods (CF) exploit the wisdom of crowds to capture deeply structured similarities in musical objects, such as songs, artists or albums. When CF is available, it frequently outperforms content-based methods in recommendation tasks. However, songs in the so-called “long tail” cannot reap the benefits of collaborative filtering, and practitioners must rely on content-base...

As political polarization in the United States continues to rise, the question of whether polarized individuals can fruitfully cooperate becomes pressing. Although diversity of individual perspectives typically leads to superior team performance on complex tasks, strong political perspectives have been associated with conflict, misinformation and a reluctance to engage with people and perspecti...

In many computational linguistic scenarios, training labels are subjectives making it necessary to acquire the opinions of multiple annotators/experts, which is referred to as ”wisdom of crowds”. In this paper, we propose a new approach for modeling wisdom of crowds based on the Latent Mixture of Discriminative Experts (LMDE) model that can automatically learn the prototypical patterns and hidd...

The process of writing textbooks is still very traditional regarding the status of authorship and expert opinions. Recently we observe the emergence of authors who follow a different approach, taping the wisdom of crowds as key resource of their own publications. In this paper, we explore business model innovation which leverages value propositions of textbooks by applying crowdsourcing. We use...

We study learning in a setting where agents receive independent noisy signals about the true value of a variable and then communicate in a network. They näıvely update beliefs by repeatedly taking weighted averages of neighbors’ opinions. We show that all opinions in a large society converge to the truth if and only if the influence of the most influential agent vanishes as the society grows. W...