Why Simulate? To Develop a Mental Model

Nowak, Andrzej; Rychwalska, Agnieszka; Borkowski, Wojciech

doi:10.18564/jasss.2235

Cited by 23 publications

(20 citation statements)

References 15 publications

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“…In such light, the focus on just two parameters ‘driving’ the opinion change: the available information and the emotional state is an obvious simplification. On the other hand, such simplification, used in a working model, may lead to potentially useful understanding of the processes—one of the major goals of the model based approach [ 84 , 85 ]. In terms it role as the splitting factor, the emotional state is less dependent on the valence of the emotions (positive or negative) than on their intensity.…”

Section: General Model Descriptionmentioning

confidence: 99%

Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015

Sobkowicz

2016

PLoS ONE

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We present results of an abstract, agent based model of opinion dynamics simulations based on the emotion/information/opinion (E/I/O) approach, applied to a strongly polarized society, corresponding to the Polish political scene between 2005 and 2015. Under certain conditions the model leads to metastable coexistence of two subcommunities of comparable size (supporting the corresponding opinions)—which corresponds to the bipartisan split found in Poland. Spurred by the recent breakdown of this political duopoly, which occurred in 2015, we present a model extension that describes both the long term coexistence of the two opposing opinions and a rapid, transitory change due to the appearance of a third party alternative. We provide quantitative comparison of the model with the results of polls and elections in Poland, testing the assumptions related to the modeled processes and the parameters used in the simulations. It is shown, that when the propaganda messages of the two incumbent parties differ in emotional tone, the political status quo may be unstable. The asymmetry of the emotions within the support bases of the two parties allows one of them to be ‘invaded’ by a newcomer third party very quickly, while the second remains immune to such invasion.

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Section: General Model Descriptionmentioning

confidence: 99%

Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015

Sobkowicz

2016

PLoS ONE

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“…When we study the possible role of mental models in policy support for climate change or other environmental sustainability initiatives, one main question arises: does the content of mental models include analogues of bio-physical variables, human behaviour, and causal relations? That is, are mental models 'a small-scale model of how the world works' (Craik 1943, Johnson-Laird 1983, Nowak, Rychwalska et al 2013, or are they composites of values and attitudes in a social psychology sense (Inayatullah 2004, Quinn 2005, Price, Walker et al 2014? In the first case, which we refer to as a 'system dynamic' view, a mental model may include, say, CO2 emissions, economic activities, sequestration processes, and mitigation initiatives and explicit assumptions about how they interact.…”

Section: Mental Models: Current Understanding and Challenges For Sustmentioning

confidence: 99%

Testing the consistency between goals and policies for sustainable development: mental models of how the world works today are inconsistent with mental models of how the world will work in the future

et al. 2016

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Understanding complex problems such as climate change is difficult for most non-scientists, with serious implications for decision-making and policy support. Scientists generate complex computational models of climate systems to describe and understand those systems and to predict the future states of the systems. Non-scientists generate mental models of climate systems, perhaps with the same aims and perhaps with other aims too. Often, the predictions of computational models and of mental models do not correspond, with important implications for human decision-making, policy support, and behaviour change. Recent research has suggested non-scientists' poor appreciation of the simple foundations of system dynamics is at the root of the lack of correspondence between computational and mental models. We report here a study that uses a simple computational model to 'run' mental models to assess whether a system will evolve according to our aspirations when considering policy choices. We provide novel evidence of a dual process model: how we believe the system works today is a function of ideology and worldviews; how we believe the system will look in the future is related to other, more general, expectations about the future. The mismatch between these different aspects of cognition may prevent establishing a coherent link between a mental model's assumptions and consequences, between the present and the future, thus potentially limiting decision-making, policy support, and other behaviour changes.

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“…It is a technique to model complex phenomena as mathematical entities so that rigorous analysis techniques can be applied on the models to understand the reality of the complex phenomenon. Moreover, formal specifications are abstract, precise and to some extent complete in nature [6], [7]. The abstraction of a formal specification allows to comprehend a complex phenomenon, where as the precise semantics eliminates ambiguity in the model.…”

Section: A Formal Modelsmentioning

confidence: 99%

Towards a Set Theoretical Approach to Big Data Analytics

Mukkamala

Hussain

Vatrapu

2014

2014 IEEE International Congress on Big Data

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Formal methods, models and tools for social big data analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by relational sociology. There are no other unified modeling approaches to social big data that integrate the conceptual, formal and software realms. In this paper, we first present and discuss a theory and conceptual model of social data. Second, we outline a formal model based on set theory and discuss the semantics of the formal model with a real-world social data example from Facebook. Third, we briefly present and discuss the Social Data Analytics Tool (SODATO) that realizes the conceptual model in software and provisions social data analysis based on the conceptual and formal models. Fourth and last, based on the formal model and sentiment analysis of text, we present a method for profiling of artifacts and actors and apply this technique to the data analysis of big social data collected from Facebook page of the fast fashion company, H&M.

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Why Simulate? To Develop a Mental Model

Cited by 23 publications

References 15 publications

Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015

Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015

Testing the consistency between goals and policies for sustainable development: mental models of how the world works today are inconsistent with mental models of how the world will work in the future

Towards a Set Theoretical Approach to Big Data Analytics

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