This seminar will be held in the Room 9.87, Worsley Building, at 12.30 on Thursday 14th November.
Seminars are free and open for all to attend. No prior booking is required.
Each presentation will be followed by a short Q&A session.
Presentation: Using novel data in applied research: a case study of housing and voting
By: Dr Nik Lomax (University of Leeds)
Abstract: There is currently much discussion and hype around the use of big data to provide insight in to a range of phenomena, from consumer behaviour to travel patterns. In this talk, I move away from the discussion of big and emerging data, to focus on recent work using what I loosely term ‘novel’ data.
These are novel in the sense that they are data which are not routinely used in academia but which can provide insight in to local level phenomena and spatial patterns. I provide two substantive examples. The first dataset comes from a commercial provider and reports the characteristics of properties in the sales and rentals market. I use these data to assess local variation in house prices and in rent/price ratios. The second dataset is provided by the UK Government’s e-petitions website. I use these data to estimate the Brexit referendum vote share for Westminster Parliamentary Constituencies and to create a classification of Constituencies based on the types of petitions constituents sign. In both examples I utilise techniques often used on big datasets alongside more conventional techniques.
The overall aim of this talk is to highlight that there are a wide range of data available which can provide insight in to spatial patterns which are not routinely used in research. Once we stop worrying about finding big datasets to solve problems, we can focus on applying useful techniques to the range of novel datasets available to us.
Biography: Nik Lomax is an Associate Professor of Data Analytics for Population Research at the University of Leeds. His research utilises existing and new forms of data to produce estimates and projections of populations and their demographic characteristics. This work includes the development of models which incorporate census, survey, administrative, micro- and commercially available datasets. He is the Co-Director of the ESRC funded Consumer Data Research Centre, which utilises consumer data to provide insight in to consumption, lifestyle and mobility behaviours.
Nik is a Turing Fellow, funded by the Alan Turing Institute for Data Science and AI, where he is developing methods based on microsimulation to integrate information on human behaviour which are lacking from current demographic models.