Chess players' performance beyond 64 squares: A case study on the limitations of cognitive abilities transfer

In a beauty contest experiment with over 6,000 chess players, ranked from amateur to world class, we found that Grandmasters act very similar to other humans. This even holds true when they play exclusively against players of approximately their own strength. In line with psychological research on chess players' thinking, we argue that they are not more rational in a game theoretic sense per se. Their skills are rather specific for their game.chess, beauty contest, cognitive transfer

Time Critical Social Mobilization: The DARPA Network Challenge Winning Strategy

It is now commonplace to see the Web as a platform that can harness the collective abilities of large numbers of people to accomplish tasks with unprecedented speed, accuracy and scale. To push this idea to its limit, DARPA launched its Network Challenge, which aimed to "explore the roles the Internet and social networking play in the timely communication, wide-area team-building, and urgent mobilization required to solve broad-scope, time-critical problems." The challenge required teams to provide coordinates of ten red weather balloons placed at different locations in the continental United States. This large-scale mobilization required the ability to spread information about the tasks widely and quickly, and to incentivize individuals to act. We report on the winning team's strategy, which utilized a novel recursive incentive mechanism to find all balloons in under nine hours. We analyze the theoretical properties of the mechanism, and present data about its performance in the challenge.Comment: 25 pages, 6 figure

Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the pattern by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game makes a decision among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information

Exploring the Effects of Aggregate Review Characteristics on Mobile Application Adoption

This study investigates how potential adopters of mobile applications utilize online review systems to inform their perceptions on the application’s technology characteristics and thus inform their eventual adoption decision. Informational cascades and herding behavior theories are combined with the Innovation Diffusion Model and the Theory of Planned Behavior (TPB) to develop a research model. The review characteristics of aggregate review valence, overall rating, and review volume are related to the perceived technology characteristics of relative advantage, compatibility, and complexity. These, in turn, use the TPB as a lens to tie it all to the behavioral intention to adopt the mobile application. An online survey yielded 448 responses for analysis. The results yield some important insights and raises new questions for future evaluation

The Dynamics of Viral Marketing

We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of recommendations and the cascade sizes, which we explain by a simple stochastic model. We analyze how user behavior varies within user communities defined by a recommendation network. Product purchases follow a 'long tail' where a significant share of purchases belongs to rarely sold items. We establish how the recommendation network grows over time and how effective it is from the viewpoint of the sender and receiver of the recommendations. While on average recommendations are not very effective at inducing purchases and do not spread very far, we present a model that successfully identifies communities, product and pricing categories for which viral marketing seems to be very effective