Staff Directory

Dr Suzy Moat

Associate Professor of Behavioural Science

Research Interests

We increasingly rely on networked computer systems and smart cards to support our everyday activities, and everything we do generates data ? whether buying bread at the supermarket, taking a ride on the Tube, or calling a friend for a chat.

This data is opening up a new era for our understanding of human behaviour ? and also for policy making and business processes which depend upon this understanding.

As a computational social scientist, my research investigates how the vast amounts of data generated by our everyday use of technology can help us understand and even predict how humans behave.

Find out more about the Computational Social Science Conference, taking place at Warwick Business School from Wed 11th June - Fri 13th June 2014.

Chairs: Suzy Moat, Mark Carrigan and Tobias Preis.

Teaching in 2015-2016

Research Students

  • IB9ES0: Advanced Communication Skills for Data Science Research

Executive MBA

  • IB9AP0: Behavioural Sciences for the Manager


  • IB9CS0: Big Data Analytics

MSc Business

  • IB9CSB: Big Data Analytics


  • IM9030: Complexity in the Social Sciences

Research Students

  • IB9ER0: Designing and Managing Data Science Research

Behavioural Science Group

Email:  /  Tel: 024 765 73197


Suzy Moat is an Assistant Professor of Behavioural Science at Warwick Business School. Her work exploits data from sources such as Google, Wikipedia and Flickr, to investigate whether data from the Internet can help us measure and even predict human behaviour.

In recent studies, in collaboration with Tobias Preis, H. Eugene Stanley and colleagues, Moat has provided evidence that patterns in searches for financial information on Wikipedia and Google may have offered clues to subsequent stock market moves, and that Internet users from countries with a higher per capita GDP are more likely to search for information about years in the future than years in the past.

Moat was awarded a Ph.D. from the University of Edinburgh and won a series of prizes during her studies. Since 2011, Moat has secured £3.3 million of funding from UK, EU and US research agencies. Her work has been featured by television, radio and press worldwide, including recent pieces on CNN and the BBC.

Moat has acted as an advisor to government and public bodies on the predictive capabilities of big data. She currently co-directs a data science research team working on these questions.

Recent media coverage of her work includes:

  • Guardian (2013)
        "Which countries are the most forward thinking? See it visualised"
  • New Scientist (2012)
        "Online searches for future linked to economic success"
  • BBC (2013)
        "Google searches predict market moves"
  • Bloomberg Businessweek (2013)
        "'Big Data' Researchers Turn to Google to Beat the Markets"
  • Wired (2013)
        "Wikipedia page views could predict stock market changes"
  • Wall Street Journal (2014)
        "Do politics-themed Google searches predict stock activity?"

  • CNN (TV interview, 2013)
  • BBC (TV interview, 2013)
  • Classic FM (radio interview, 2013)
  • Newstalk Ireland (radio interview, 2013)

  • Interview with Women in Business magazine (2013)

    You can follow Suzy on Twitter at @suzymoat

  • Recent Publications

    Journal Articles

    Book Chapters

    • Preis, T. & Moat, H. S. "Early signs of financial market moves reflected by Google Searches"
      Social Phenomena: From Data Analysis to Models (2015): 89-102.
    • Moat, H.S., Curme, C., Stanley, H. E., & Preis, T. "Anticipating stock market movements with Google and Wikipedia"
      Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale (2014): 47-59.

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    What's the big deal about big data?: The potential of Big Data to help identify links between data from the real and online world is immense according to Suzy Moat and Tobias Preis of Warwick Business School.

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