This paper presents an attempt to study and monitor the evolution of research on prediction
markets (PM). It provides an extended literature review and classification scheme. The …

We discuss models and data of crowd disasters, crime, terrorism, war and disease
spreading to show that conventional recipes, such as deterrence strategies, are often not …

In this essay, we consider the role of Big Data in the public sector. Motivating our work is the
recognition that Big Data is still in its infancy and many important questions regarding the …

We analyze the extent to which simple markets can be used to aggregate disperse
information into efficient forecasts of uncertain future events. Drawing together data from a …

In addition to being environment friendly, vehicle-to-grid (V2G) systems can help the plug-in
electric vehicle (PEV) users in reducing their energy costs and can also help stabilizing …

In the practice of point prediction, it is desirable that forecasters receive a directive in the
form of a statistical functional. For example, forecasters might be asked to report the mean or …

Traditional groups meetings are an inefficient and ineffective method for making forecasts
and decisions. We compare two structured alternatives to traditional meetings: the Delphi …

In this paper we review methods that aim to aid the anticipation of rare, high-impact, events.
We evaluate these methods according to their ability to yield well-calibrated probabilities or …

The automated computer programs using data mining and predictive technologies do a fare
amount of trades in the markets. Data mining is well founded on the theory that the historic …

Collective intelligence is the ability of a group to perform more effectively than any individual
alone. Diversity among group members is a key condition for the emergence of collective …