P-MART: Towards a classification of online prediction markets

  • Dorit Geifman University of Haifa
  • Daphne Ruth Raban University of Haifa
  • Rafaeli Sheizaf University of Haifa
Keywords: Prediction Markets, Classification, Collective Intelligence

Abstract

Prediction Markets are a family of Internet–based social computing applications, which use market price to aggregate and reveal information and opinion from dispersed audiences. The considerable complexity of these markets inhibited the full realization of the promise so far. This paper offers the P–MART classification as a tool for organizing the current state of knowledge, aiding the construction of tailored markets, identifying ingredients for Prediction Markets’ success and encouraging research. P–MART is a dual–facet classification of implementations of Prediction Markets describing traders and markets. The proposed classification framework was calibrated by examining a variety of real–world online implementations. A publicly accessible wiki resource accompanies this paper in order to stimulate further research and future expansion of the classification.

Author Biographies

Dorit Geifman, University of Haifa
Doctoral Candidate at the Graduate School of Management, University of Haifa and active in in the Sagy Center for Internet Research
Daphne Ruth Raban, University of Haifa
Lecturer at the Graduate School of Management, University of Haifa and a member of the Sagy Center for Internet Research.
Rafaeli Sheizaf, University of Haifa
Director of the Sagy Center for Internet Research and Head of the Graduate School of Management, University of Haifa.
Published
2011-06-28
How to Cite
Geifman, D., Raban, D. R., & Sheizaf, R. (2011). P-MART: Towards a classification of online prediction markets. First Monday, 16(7). https://doi.org/10.5210/fm.v16i7.3203