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Voice * Entrepreneurship and Innovation * Leading an Agile and Resilient Organisation * Leading Digital Transformation * Leading People Through Change and Disruption * Marketing Strategy and Planning * Platform Strategy * Strategic Choices * Strategy Execution * The Strategic Mindset of Leadership * Build your own qualification * Working with WBS * Overview * Early Careers Recruitment * Student Consultancy Projects * MBA and Experienced Hires * Develop your top talent * News * Latest WBS News * Core Insights * Podcasts * Core Magazine * Media Enquiries * Blogs * Latest Blogs * Staff Blogs * Undergraduate Blogs * Master's Blogs * MBA Blogs * Executive Education Blogs * Doctoral Blogs * Events * Latest Events * Alumni * Overview * Alumni Stories * Mentoring Programme * Giving Back to WBS * Professional Networks * Geographical Networks * * My.WBS Staff Directory * Staff Directory * The Dean, Professor Andy Lockett * The Board of WBS * Senior Management Group * Job vacancies * Home * About Us * People * Professor Suzy Moat Professor Suzy Moat Professor of Behavioural Science 0> (Behavioural Science Group) Suzy.Moat@wbs.ac.uk 024 765 73197 3.116 Suzy.Moat@wbs.ac.uk 024 765 73197 3.116 Suzy Moat is Professor of Behavioural Science at Warwick Business School, where she co-directs the Data Science Lab. She is also a Fellow of The Alan Turing Institute. Her research investigates whether data on our usage of the Internet, from sources such as Google, Wikipedia and Flickr, can help us measure and even predict human behaviour in the real world. Moat's work touches on problems as diverse as linking online behaviour to stock market moves (with Preis, Curme, Stanley, et al.), estimating crowd sizes (with Botta and Preis) and evaluating whether the beauty of the environment we live in might affect our health (with Seresinhe and Preis). The results of her research have been featured by television, radio and press worldwide, by outlets such as CNN, BBC, The Guardian, Wall Street Journal, New Scientist and Wired. Moat studied Computer Science at UCL and Psychology at the University of Edinburgh and won a series of prizes during her studies. With her collaborator and Data Science Lab co-director Tobias Preis, she led an online course on using big data to measure and predict human behaviour which has attracted over 25,000 learners to date. Moat has also acted as an advisor to government and public bodies on the predictive capabilities of big data. Selected 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" Wired (2013) "Wikipedia page views could predict stock market changes" Wall Street Journal (2014) "Do politics-themed Google searches predict stock activity?" BBC (2015) "Crowds 'could be counted' with phone and Twitter data CNN (TV interview, 2013) BBC (TV interview, 2013) Interview with Women in Business magazine (2013) Interview with TechMix magazine (2014) You can follow Suzy on Twitter at @suzymoat and see her publications on Google Scholar. 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. In June 2014, I chaired Europe's first Computational Social Science Conference with Mark Carrigan and Tobias Preis. Sign up to hear about future runs of our FutureLearn MOOC, Big Data: Measuring and Predicting Human Behaviour! LATEST JOURNAL ARTICLES * FASTER INDICATORS OF CHIKUNGUNYA INCIDENCE USING GOOGLE SEARCHES Miller, S., Preis, T., Mizzi, G., Bastos, L. S., Gomes, M. F. d. C., Coelho, F. C., Codeço, C. T. and Moat, H. S. 2022 PLOS Neglected Tropical Diseases, 16, 6, e0010441 * SCENICNESS ASSESSMENT OF ONSHORE WIND SITES WITH GEOTAGGED PHOTOGRAPHS AND IMPACTS ON APPROVAL AND COST-EFFICIENCY McKenna, R., Weinand, J. M., Mulalic, I., Petrović, S., Mainzer, K., Preis, T. and Moat, H. S. 2021 Nature Energy, 6, 663-672 * MEASURING THE SIZE OF A CROWD USING INSTAGRAM Botta, F., Moat, H. S. and Preis, T. 2020 Environment and Planning B: Urban Analytics and City Science, 47, 9, 1690-1703 * SENSING GLOBAL TOURISM NUMBERS WITH MILLIONS OF PUBLICLY SHARED ONLINE PHOTOGRAPHS Preis, T., Botta, F. and Moat, H. S. 2020 Environment and Planning A: Economy and Space, 52, 3, 471-477, 0308518X1987277 Load more (31) CONFERENCE ITEM * ESTIMATING TOURISM STATISTICS WITH WIKIPEDIA PAGE VIEWS Alis, C. M., Letchford, A., Moat, H. S. and Preis, T. 2015 WebSci '15 Proceedings of the ACM Web Science Conference, 33, 1-2 * Edit your staff profile How to edit this staff profile data. Editing your staff data WBS staff profiles are created from data stored in a number of databases. If your profile needs updating, the data comes from the following places: WBS databases: Centrally-managed data Name: Managed by WBS Human Resources department. Please contact WBS Human Resources. 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