Artificial prediction markets as a tool for syndromic surveillance

Fatemeh Jahedpari, Julian Padget, Marina De Vos, Benjamin Hirsch

Research output: Contribution to journalConference articlepeer-review


A range of data sources across the internet, such as google search terms, twitter topics and Facebook messages, amongst others, can be viewed as kinds of sensors from which information might be extractable about trends in the expression of matters of concern to people. We focus on the problem of how to identify emerging trends after the original textual data has been processed into a quantitative form suitable for the application of machine learning techniques.We present some preliminary ideas, including an agent-based implementation and some early results, about the application of artificial prediction markets to such data, taking the specific domain of syndromic surveillance (early stage recognition of epidemics) as an example, using publicly available data sets.

Original languageEnglish
Pages (from-to)113-126
Number of pages14
JournalCEUR Workshop Proceedings
Publication statusPublished - 9 Jan 2014
EventSintelnet WG5 Workshop on Crowd Intelligence: Foundations, Methods, and Practices, CROWD 2014 - Barcelona, Catalonia, Spain
Duration: 8 Jan 20149 Jan 2014

ASJC Scopus subject areas

  • General Computer Science


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