![\"\"](\"https:\/\/cfpm.org\/qual2rule\/wp-content\/uploads\/2013\/09\/Qual2Rule-Diagram.gif\")
<\/p>\n","protected":false},"excerpt":{"rendered":"
\n<\/p>\n
This blog is the official mouthpiece of the European Social Simulation Association\u2018s Special Interest Group on this topic.<\/p>\n
Many academics consider qualitative evidence (e.g. texts gained from transcribing someone talking or observations of people) and quantitative evidence to be incommensurable.\u00a0 However agent-based simulations are a possible vehicle for bridging this gap.\u00a0 Narrative textual evidence often gives clues as to the in-context behaviour of individuals and is thus a natural source for behaviours to inform the specification of corresponding agent behaviour within simulations.\u00a0 They will not give a complete picture of this, but they will provide some of \u201cmenu\u201d of behaviours that people use.\u00a0 Once specified, a simulation model can be run and the results measured \u2013 cross validating the result (Moss & Edmonds 2005).\u00a0 The simulation provides the concrete instantiation of the connection between the mico-level behaviours and macro-level outcomes.\u00a0 Thus such simulations are a well-founded route to integrating qualitative and quantitative evidence.<\/p>\n
Some modellers have used informal conversations to inform their modelling (e.g. Moss 1998), but a key advance came with the theses of Taylor (2003) and Bharwani (2004).\u00a0 They both transcribed interviews into textual records and then tried to systematically analyse those transcripts to inform their simulation specification.\u00a0 Although the process of analysing natural language data is never going to be a completely formal or automatic process, relying as it does upon the understanding of the interviewer and\/or analyst, formalising the \u201cprocess\u201d makes it more transparent and replicable.\u00a0 The data can be made available and examined by subsequent researchers who may spot aspects that the original observer has missed, as well as seeing how the sense of the stakeholder might have been changed during the process.\u00a0 Unlike an informal approach, which does not work from transcribed text, a subsequent researcher can follow the chain of analysis and understand it better.<\/p>\n
In this SIG we hope to further understanding of how to do this better.\u00a0 It is open to all approaches that seek to move from qualitative evidence towards a simulation in a systematic way.\u00a0 This includes, but is not limited to:<\/p>\n
*\u00a0 Approaches based in Grounded Theory.<\/p>\n
*\u00a0 Tools for facilitating such a process.<\/p>\n
*\u00a0 Participatory processes that result in a simulation.<\/p>\n
*\u00a0 Frameworks for aiding the analysis of text into rules.<\/p>\n
*\u00a0 Elicitation techniques that would aid the capture of information in an appropriate structure.<\/p>\n
*\u00a0 Models and ideas from psychology to aid in the above process.<\/p>\n
*\u00a0 Insights and tools from Natural Language processing that may help this process.<\/p>\n
*\u00a0 Agent architectures that will facilitate the programming of agents from such analyses.<\/p>\n
*\u00a0 Philosophical or Sociological critiques of this project, pointing out assumptions and dangers.<\/p>\n
*\u00a0 Examples of where this approach has been tried.<\/p>\n
Activities of this group of people have included: an informal workshop in Manchester in September 2012 (http:\/\/cfpm.org\/qual2rule\/informal-workshop), a special track on this topic at the ESSA conference in Warsaw 2013 (http:\/\/essa2013.org), some of which are on-line (http:\/\/cfpm.org\/qual2rule\/sessionessa-201) and others published in the Springer book \u201cAdvances in Social Simulation\u201d (http:\/\/www.springer.com\/engineering\/computational+intelligence+and+complexity\/book\/978-3-642-39828-5), an upcoming special issue\/section of JASSS (http:\/\/jasss.soc.surrey.ac.uk), and of course this blog.<\/p>\n
We plan to organise special tracks at future conferences, for example at \u201cSocial Simulation 2014\u2033 in Barcelona (http:\/\/www.essa2014.eu), to post any relevant news of papers, events here, and any other activities that its members suggest\/organise.<\/p>\n
For all queries associated with this SIG (for example wishing to join, or wanting the ability to post to this blog) please contact the SIG organiser: Melania Borit, Univeristy of Tromso, Norway.<\/p>\n
References<\/p>\n
* Bhawani, S. (2004) Adaptive Knowledge Dynamics and Emergent Artificial Societies: Ethnographically Based Multi-Agent Simulations of Behavioural Adaptation in Agro-Climatic Systems. Doctoral Thesis, University of Kent, Canterbury, UK. http:\/\/cfpm.org\/qual2rule\/Sukaina%20Bharwani%20Thesis.pdf<\/p>\n
* Moss, S. (1998) Critical Incident Management: An Empirically Derived Computational Model. Journal of Artificial Societies and Social Simulation 1(4):1. http:\/\/jasss.soc.surrey.ac.uk\/1\/4\/1.html<\/p>\n
* Taylor, R.I. (2003). Agent-Based Modelling Incorporating Qualitative and Quantitative Methods: A Case Study Investigating the Impact of E-commerce upon the Value Chain. Doctoral Thesis, Manchester Metropolitan University, Manchester, UK. http:\/\/cfpm.org\/cpmrep137.html<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
This blog is the official mouthpiece of the European Social Simulation Association\u2018s Special Interest Group on this topic. Many academics consider qualitative evidence (e.g. texts gained from transcribing someone talking or observations of people) and quantitative evidence to be incommensurable.\u00a0 However agent-based simulations are a possible vehicle for bridging this gap.\u00a0 Narrative textual evidence often … Continue reading ESSA SIG<\/span>