Centre for Policy Modelling News

News from the Centre for Policy Modelling, including announcements of: new papers, special issues, books, workshops, projects, jobs and study opportunities.

01 October, 2016

Some Results of the SCID project: Staging Abstraction of Complex Simulations


One of the key ideas behind the "SCID project" http://cfpm.org/scid (Social Complexity of Immigration and Diversity) is that of starting with a simulation that reflects the evidence and what is known about the social model being modelled, however complex this makes it. *Then*, doing a simpler model of this complex model to get understanding of that model (and indeed models of the model of the complex model etc.). In this way we can stage abstraction rather than attempting it in one leap. This retains reference between the models, allows those doing the simplification free reign in what they simplify (under the constraint it has to match the significant results of the more complex model), and combines some of the advantages of rigour _and_ relevance.

This is described in three papers, one for each modelling stage (all Open Access):
Fieldhouse, E; Lessard-Phillips, L; and Edmonds, B. (2016) Cascade or echo chamber? A complex agent-based simulation of voter turnout. Party Politics. 22(2):241-256.  DOI:10.1177/1354068815605671
This describes a complex model of voter behaviour that includes all the processes thought to be relevant to whether people vote.  This is the first stage of abstraction from evidence and data to descriptive simulation. The model itself can be found and downloaded from http://www.openabm.org/model/4368
Lafuerza LF, Dyson L, Edmonds B, McKane AJ (2016) Staged Models for Interdisciplinary Research. PLoS ONE, 11(6): e0157261. doi:10.1371/journal.pone.0157261
(But please read the correction at the start since PLoS messed up the formatting and they don't fix the main paper after publication!_. A better formatted version is at: http://arxiv.org/abs/1604.00903)

This described the second stage of abstraction, from complex simulation to a simpler one that can be investigated more thoroughly. This reveals some hypotheses about the model that would not have otherwise have been discovered.
Lafuerza, LF, Dyson, L, Edmonds, B & McKane, AJ (2016) Simplification and analysis of a model of social interaction in voting, European Physical Journal B, 89:159. DOI:10.1140/epjb/e2016-70062-2
Describes a further simplification stage from simpler simulation model to analytic model.

05 July, 2016

Sad to announce the death of Rosaria Conte

I have just heard that Rosaria Conte passed away last night after a long fight with cancer. Rosaria was one of the founders of the field of social simulation, arguing for the importance of representing cognitive aspects and the impact of immerence (the impact of society upon the individual). She was very active in encouraging the field, a warm person who was always willing to discuss and argue issues out in an impassioned but friendly manner.

for more about her see: http://labss.istc.cnr.it/people/rosaria-conte

 A picture of me and Rosaria in 2008 at ISTC in Rome, pictured with my Grandson's 'Class Teddy'


04 July, 2016

Review of "The Aqua Book: Guidance on Producing Quality Analysis for Government"

In JASSS at http://jasss.soc.surrey.ac.uk/19/3/reviews/7.html

This reviews the useful work done by government modellers in developing standards for policy analysis, and well as discusses it within the context of how policy actors 'use' policy models and modellers.

09 June, 2016

Welcome to Shaheen Syed...

...who is a new Marie-Curie Early Stage Researcher, as part of the SAF21 ITN project.

Shaheen Syed

Thesis: Text Analytics for the 21st Century Fisheries


Since the 90s, it has been well-known that unstructured and semi-structured data constitute up to 90% of an organization’s data volume. The unprecedented growth of the Web and social media since then has only further increased the relative amount of unstructured and semi-structured data.

A great way to analyze this largely unstructured textual data is text analytics. Techniques such as sentiment analysis and named entity recognition are heavily being used in all sorts of research institutions and private companies. It enables the extraction of opinions on a given subject, create structured data from unstructured data, uncover other types of potential wealth and a lot more. It is a relatively new field of study and some amazing insights have already been found in e.g. Economics or Biology once they adopted text analytics.

My PhD research is aimed at implementing text analytics techniques into the fisheries domain as a whole. That is, we are investigating to what extent text analytics can be applied within the fisheries domain to gain more in-depth knowledge about fisheries and its e.g. stakeholders by utilizing quantitative computer science text mining techniques such as natural language processing and machine learning. A high degree of emphasis is placed on the investigation of different methods belonging to the same technique. This makes the various studies somewhat more explorative. However, some emphasis is placed on the predictive power of text analytics for the fisheries domain in the final stages of this PhD.