The latest outputs from researchers, alumni and friends at the UCL Centre for Advanced Spatial Analysis (CASA).
Continuing our work on machine learning and agent-based modeling, at the upcoming Computational Social Science (CSS 2020) annual conference, Dale Brearcliffe and myself have a paper entitled: “Creating Intelligent Agents: Combining Agent-Based Mo…
Continue reading »Continuing our work on machine learning and agent-based modeling, at the upcoming Computational Social Science (CSS 2020) annual conference, Dale Brearcliffe and myself have a paper entitled: “Creating Intelligent Agents: Combining Agent-Based Mo…
Continue reading »While in previous posts we have discussed machine learning (ML) with respect to social media analysis, we have also been exploring how one can use it in agent-based modeling. One of the first examples of this is a new paper with Paul Cummings which has…
Continue reading »While in previous posts we have discussed machine learning (ML) with respect to social media analysis, we have also been exploring how one can use it in agent-based modeling. One of the first examples of this is a new paper with Paul Cummings which has…
Continue reading »Anna and I have a new CEP Discussion Paper out looking at innovation and productivity in UK firms. Read it here.It’s quite technical. Working with the data science firm Growth Intelligence, we combine rich administrative info with media text and machin…
Continue reading »Following on from our work on bots and health discussions in relation to online social networks (OSNs), Xiaoyi Yuan, Ross Schuchard and myself have just published a paper entitled “Examining Emergent Communities and Detecting Social Bots within the Pol…
Continue reading »My PechaKucha talk at DataBeers : “Visualizing Geolocated Tweets: a Spatial Data Mining Approach”.
Inspired by @jeroenhjanssens, author of the Data Science Toolbox, I decided to give a go to one of the most unfriendly data sources: An XML API. Apart from its rich syntax with query capabilities, I tend think XML is highly … Continue reading →
Recently I have been looking into different algorithms for the clustering geospatial data. The problem of finding “similar” regions in space, is a very interesting one, since this type of classification enables a whole range of applications (e.g.: urban development, … Continue reading →