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This volume analyses, from a computational point of view, how culture may arise, develop and evolve through time. The four sections in this book examine and analyse the modelling of culture, group and organisation culture, culture simulation, and culture-sensitive technology design. Different research disciplines have different perspectives on culture, making it difficult to compare and integrate different concepts and models of culture. By taking a computational perspective this book nevertheless enables the integration of concepts that play a role in culture, even though they might originate from different disciplines. Culture is usually regarded as something vague and qualitative and thus difficult to deal with in a computational and formal setting. Taking a computational approach to culture thus encompasses a twofold risk: taking a too simplistic approach to cultural influence on behaviour; or trying to capture too much, hence not leading to useful computational tools. However, the approaches and insights in this collection show how different perspectives by leading researchers described in thirteen chapters still can form a coherent picture. The book thus illustrates the potential of using computing systems to better understand culture. By describing methods, theories and concrete application results about the integration of cultural aspects into computer systems, this book provides inspiration to researchers of all disciplines alike and presents the start of an interdisciplinary dialogue on culture

This volume analyses, from a computational point of view, how culture may arise, develop and evolve through time. The four sections in this book examine and analyse the modelling of culture, group and organisation culture, culture simulation, and culture-sensitive technology design. Different research disciplines have different perspectives on culture, making it difficult to compare and integrate different concepts and models of culture. By taking a computational perspective this book nevertheless enables the integration of concepts that play a role in culture, even though they might originate from different disciplines. Culture is usually regarded as something vague and qualitative and thus difficult to deal with in a computational and formal setting. Taking a computational approach to culture thus encompasses a twofold risk: taking a too simplistic approach to cultural influence on behaviour; or trying to capture too much, hence not leading to useful computational tools. However, the approaches and insights in this collection show how different perspectives by leading researchers described in thirteen chapters still can form a coherent picture. The book thus illustrates the potential of using computing systems to better understand culture. By describing methods, theories and concrete application results about the integration of cultural aspects into computer systems, this book provides inspiration to researchers of all disciplines alike and presents the start of an interdisciplinary dialogue on culture.

Although there have been many simulations of ecological systems that include social aspects of the persons involved, very little have considered the social aspects of the communities themselves as a separate system. In this paper we will integrate social, economic and ecological models in order to simulate a more realistic shery community. We need this type of integrated model when we want to explore the effects of new fishing policies on these communities. We argue that a value based approach for the agents is essential and show how this can be used to integrate the different systems. ; presentation at the Social Simulation Conference 2017, Dublin, Ireland. The first author has received funding from the European Union's Horizon 2020 Framework Programme Marie Sk lodowska-Curie (MSC) - ITN - ETN programme (project 642080).

Intro -- Preface -- Organization -- Contents -- The Determinants of Social Connectedness in Europe -- 1 Introduction -- 2 Data -- 3 Determinants of European Social Connectedness -- 4 Conclusion -- References -- Combining Language Models and Network Features for Relevance-Based Tweet Classification -- 1 Introduction -- 2 Related Work -- 3 Data -- 4 Methods -- 4.1 Text Classification -- 4.2 Network Features -- 4.3 Ensemble Model -- 4.4 Evaluation -- 5 Results -- 5.1 Content-Based Tweet Classification -- 5.2 Results Ensemble Model -- 5.3 Analysis of User Rank Contribution to Tweet Relevance -- 6 Conclusions -- References -- Co-spread of Misinformation and Fact-Checking Content During the Covid-19 Pandemic -- 1 Introduction -- 2 Related Work -- 2.1 Misinformation Spread Analysis -- 2.2 Fact-Checking Information Spread -- 3 Co-spread of Misinformation and Corrective Information During the Covid-19 Pandemic -- 3.1 Dataset -- 3.2 Analysed Periods Generation -- 4 Multivariate Spread Variance Analysis -- 4.1 Experimental Setup -- 4.2 Results -- 5 Fact-Checking Misinformation Impact Analysis -- 5.1 Experimental Setup -- 5.2 Results -- 6 Discussion -- 7 Limitations and Future Work -- 8 Conclusion -- References -- Facebook Ads: Politics of Migration in Italy -- 1 Introduction -- 2 Background -- 3 Data -- 4 Results -- 4.1 Characterizing Advertising Around Migration -- 4.2 Audience Targeting -- 5 Discussion -- A Appendix -- References -- It's Not Just About Sad Songs: The Effect of Depression on Posting Lyrics and Quotes -- 1 Introduction -- 2 Background -- 3 Data Collection and Preparation -- 3.1 myPersonality Dataset -- 3.2 Identifying Quotes in User Timelines -- 4 Quotes/Lyrics and Depressive Symptom Levels -- 4.1 Frequency and Sentiment of Quotes and Lyrics -- 4.2 Sentiment of Quotes -- 4.3 Themes in Quotes -- 5 Discussion and Conclusion -- References.

We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz's theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different 'value-scenarios', stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform (interactive website) for decision-makers to understand the trade-offs in policies for government and non-government organizations.

The difficulty of learning to program has long been identified amongst novices. This study explored the benefits of teaching a problem solving strategy by comparing students' perceptions and attitudes towards problem solving before and after the strategy was implemented in secondary schools. Based on self-efficacy theory, students' problem solving self-efficacy as well as teachers' self-efficacy were investigated, showing that both students' and teachers' self-efficacy may have benefited from the explicit instruction. This would imply that teaching problem solving explicitly should be encouraged to increase self-efficacy to program.

We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz's theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different 'value scenarios', stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform (interactive website) for decision-makers to understand the trade-offs in policies for government and non-government organizations.

During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions. ; Correction available: https://link.springer.com/article/10.1007%2Fs11023-021-09565-8 (WOS:000671651200001)

During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions.