18-20 March 2015
Cologne University of Applied Sciences, Germany
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Quantifying human behaviour with Internet data
University of Warwick, United Kingdom
Our everyday usage of the Internet generates huge amounts of data on how humans collect and exchange information worldwide. In this talk, I will outline recent work in which we investigate whether data from sources such as Google, Wikipedia and Flickr can be used to measure and even predict real world human behaviour. I will provide case studies from the economic domain and beyond.
Suzy Moat is an Assistant Professor of Behavioural Science at Warwick Business School. 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.
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