Using Agent Based Modelling to Integrate Data on Attitude Change

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This article has two goals. Firstly, it shows how a relatively novel technique (Agent Based Modelling, hereafter ABM) can integrate different data types that are often used only in separate strands of research (interviews, experiments and surveys).
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  [ad2anonrev.doc] 1 Using Agent Based Modelling to Integrate Data on Attitude Change Abstract This article has two goals. Firstly, it shows how a relatively novel technique (Agent Based Modelling, hereafter ABM) can integrate different data types that are often used only in separate strands of research (interviews, experiments and surveys). It does this by comparing a well-known ABM of attitude dynamics with an alternative model using data from surveys and experiments. Secondly, the article explains ABM methodology and why it is important to the distinctiveness of ABM as a research method. In particular, the ramifications of differing approaches to ABM calibration and validation are discussed using the two different ABM as examples. The article concludes by showing how ABM might provide a progressive research strategy for integrating different data types and thus different disciplines in attitude research. Keywords : Attitude Change, Agent-Based Modelling, Social Influence, Relative Agreement Model, Deffuant, NetLogo, Mixed Methods. Introduction It is a commonplace in sociology that research tends to be conducted either qualitatively or quantitatively and that each approach finds it hard to engage directly with the other. 1  This article demonstrates why and how ABM might be able to integrate qualitative and quantitative data into unified theories. To do this, however, it is necessary to introduce the relatively unfamiliar ABM approach and explain its distinctive methodology. As a case study to structure the discussion the article compares two attitude dynamics ABM. The first is the  [ad2anonrev.doc] 2 well-known Relative Agreement Interaction (hereafter RAI) model developed by Deffuant and others. 2  The second ABM was developed to show improved fit with quantitative attitude data by incorporating other kinds of social science research (like experimental results on social influence). These examples also provide an opportunity to show concretely how ABM work and why the methodological issues raised bear on the actual conduct of effective ABM research. It is hoped that this example led approach will make the article both accessible and germane to readers with no previous ABM experience. The comparison of particular ABM also provides a starting point for the concluding discussion of ABM as a research strategy that can progressively integrate diverse forms of data and thus promote genuinely interdisciplinary research. 3  The structure of the article is as follows. The next section provides a basic introduction to ABM and its methodology. The following section illustrates points made in this introduction  by presenting the RAI model as a typical example of a well-regarded ABM. The fourth section considers different possible relations between ABM and data and their implications. The fifth section looks at real attitude data from the British Social Attitude Survey and experimental data on social influence and considers its implications for the RAI model. The sixth section considers social processes whose absence from the RAI model might be expected to have a significant effect on its behaviour (particularly the role of the news media). The diversity of these processes also illustrates the need for a research method (like ABM) that can integrate diverse interdisciplinary data. The seventh section presents an ABM based on data from social influence experiments and incorporating a simple description of the role  played by the news media, showing that this produces improved fit with the BSAS data. The concluding section sums up the role of data and ABM methodology in progressively bridging  [ad2anonrev.doc] 3 the gap between our (largely qualitative) knowledge of small-scale social interaction and our (frequently quantitative) knowledge of aggregate social attitudes. A Very Brief Introduction to ABM and Its Methodology  The distinctiveness of ABM can best be presented in terms of two related aspects, both of which are effectively illustrated by contrast with methods of research already widely used in sociology (but also in other social sciences). Broadly speaking, quantitative research uses numbers in its data collection, analysis and theory building. To take a simple example, a regression analysis involves finding associations between numerical values collected using surveys where non-numerical data will be converted into a numerical form. 4  Success in finding meaningful associations is also presented numerically (in terms of the size and sign of model parameters, significance tests, R-squared and so on.) To present a relevant example, we might have survey data on variables like gender, ethnicity and education and also on attitudes. Using simple regression, we might find that education had the most important effect on attitudes regarding abortion but was qualified (not surprisingly) by both gender and ethnicity. 5  By contrast, qualitative research operates on narratives or texts (interviews, documents and field notes) but also argues  narratively from these to generalisations. 6  For example, Siraj (2009) analyses interview data to show how Muslims use arguments drawing on theology and traditional gender roles to justify and maintain negative attitudes to homosexuality. On the  purely descriptive level then, we might say that the difference between simulation and existing quantitative and qualitative approaches is that simulation involves representing accounts of social processes as computer programmes rather than equations or narratives. (For more detail on exactly what this entails – and further arguments supporting the claims made in this brief introduction generally – the reader is referred to the much less compressed  [ad2anonrev.doc] 4 exposition in [PLACEHOLDER REFERENCE 1].) However, matters are slightly more complicated than this and the implications turn out to be rather important. The distinctive contribution of ABM also relies on not confusing it with older and perhaps better-known simulation approaches. This is because these approaches do not really represent social  processes in a distinctive way. Instead, they just instantiate  existing kinds of theory differently. The most widely known example (which is also the easiest to explain) is probably System Dynamics (Forrester 1971). In this approach, a computer is used to establish the consequences of a set of dynamic equations. 7  However, for social scientists sceptical that equations are adequately rich and flexible to represent human behaviour, a computer  programme consisting of such equations is no more convincing as a theory than the same equations on paper. All that differs is how they are processed. Thus System Dynamics may resolve technical issues with establishing how systems of equations behave but it doesn’t address the epistemological and methodological challenges of representing human behaviour in terms of equations in the first place. 8  This point leads us towards the second aspect of ABM distinctiveness. ABM do not simply translate existing theories (whether equation or narrative based) into computer programmes  but start with the idea of representing social actors directly (rather than in terms of quantitative relationships or theoretical constructs) as they interact with each other and with their environment. Each agent is represented as a separate element of a computer programme that may have its own distinctive knowledge, point of view, thinking processes and capabilities. The simulated environment can respond to agents according to their properties or actions (a small agent can climb through a narrow window but a big one cannot, if you push at a rock it may fall on you) and agents can respond to each other on the basis of both their own mental processes and the properties and behaviour of others. (I am rude to my friends  [ad2anonrev.doc] 5 and polite to strangers. He is rude to strangers and polite to friends. She is polite to everyone except those who are rude to her.) The series of interactions between agents and between agents and the environment instantiated by an ABM corresponds to a relatively intuitive  process based specification of sociality that is often used informally by social scientists. For example, first a job is advertised, then people may see the advert and apply (or hear about it through their social networks), then candidates are short listed, then they are interviewed, then an offer is made to the preferred candidate. (But only the least promising candidates may actually arrive for interview or the preferred candidate may not accept so the job may have to  be re-advertised or it may be necessary for the employer to consider how far down the list of runner up candidates they are prepared to make a job offer.) To say that ABM represents social processes directly might seem philosophically and epistemologically contentious but what it means for my purposes is just that the computer programme represents relatively unproblematic (though not necessarily true) claims about social behaviour (the applicant considers job offers and selects the best based on wage, the forager wanders randomly looking for food) as opposed to representing theorised relationships – “suicide rate this year is associated in fixed proportions with suicide rate last year and average temperature this year” or theoretical constructs which may or may not be measurable – “individuals always act to reduce cognitive dissonance”. 9  Because ABM directly represents social processes as sequences of interactions (rather than  just instantiating existing theories) it gives rise to a distinctive methodology. When a regression analysis is performed, the object is to find the line that best fits the data according to statistical criteria. In this context, it makes little sense to distinguish between individual  properties (the data) and aggregate ones (the slope of the line). The slope of the line just is  the  best summary and could not be otherwise for that data given the prevailing statistical criteria.
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