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Modelling and Prediction of Human Behaviour (Map-HB)
Our goal is to devise new methods and techniques for modelling, understanding and predicting human behaviour from large datasets.
Our methods come from theoretical computer science (approximation algorithms, combinatorial optimisation), network science, applied mathematics and statistics.
new measure-adjusted p-error- to compare time-series that work on ‘peaky’ data, allowing for local time permutations
new mathematical model for innovation diffusion (combining Ordinary Differential Equations globally with agent-based modelling locally)
Smart energy solutions
Energy maps for small and medium enterprises (SMEs) – 3 papers, RAE project, myaems.com
Modelling of Low voltage networks – 7 papers, video
short term forecasting (SpringerBriefs book)
Measuring effects of storm naming in press, traffic and on Twitter (MetApps journal paper, the research was mentioned on ITV Meridian News on 31/05/2019)
Rumours on Twitter
Modelling spread of mood on Twitter
Wellbeing interventions in social networks
Modelling conversations on Twitter
Political debate data analytics, clustering and visualisation