Showing papers on "Social dynamics published in 2018"

A Tutorial on Modeling and Analysis of Dynamic Social Networks. Part II

Abstract: Recent years have witnessed a significant trend towards filling the gap between Social Network Analysis (SNA) and control theory. This trend was enabled by the introduction of new mathematical models describing dynamics of social groups, the development of algorithms and software for data analysis and the tremendous progress in understanding complex networks and multi-agent systems (MAS) dynamics. The aim of this tutorial is to highlight a novel chapter of control theory, dealing with dynamic models of social networks and processes over them, to the attention of the broad research community. In its first part [1], we have considered the most classical models of social dynamics, which have anticipated and to a great extent inspired the recent extensive studies on MAS and complex networks. This paper is the second part of the tutorial, and it is focused on more recent models of social processes that have been developed concurrently with MAS theory. Future perspectives of control in social and techno-social systems are also discussed.

The demographics of decarbonizing transport: The influence of gender, education, occupation, age, and household size on electric mobility preferences in the Nordic region

Abstract: Many researchers, policymakers and other stakeholders have explored and supported efforts to transition towards more sustainable forms of low-carbon mobility. Often, discussion will flow from a narrow view of consumer perceptions surrounding passenger vehicles—presuming that users act in rationalist, instrumental, and predictable patterns. In this paper, we hold that a better understanding of the social and demographic perceptions of electric vehicles (compared to other forms of mobility, including conventional cars) is needed. We provide a comparative and mixed methods assessment of the demographics of electric mobility and stated preferences for electric vehicles, drawing primarily on a survey distributed to more than 5000 respondents across Denmark, Finland, Iceland, Norway and Sweden. We examine how gender influences preferences; how experience in the form of education and occupation shape preferences; and how aging and household size impact preferences. In doing so we hope to reveal the more complex social dynamics behind how potential adopters consider and calculate various aspects of conventional mobility, electric mobility, and vehicle-to-grid (V2G) systems. In particular, our results suggest that predominantly men, those with higher levels of education in full time employment, especially with occupations in civil society or academia, and below middle age (30–45), are the most likely to buy them. However, our analysis also reveals other market segments where electric vehicles may take root, e.g. among higher income females and retirees/pensioners. Moreover, few respondents were orientated towards V2G, independent of their demographic attributes. Our empirical results can inform ongoing discussions about energy and transport policy, the drivers of environmental change, and deliberations over sustainability transitions.

Conceptualizing development in information and communication technology for development (ICT4D)

Abstract: ICT4D research is faced with the challenge of rapidly changing technologies and increasingly complex social dynamics and development processes. We argue that ICT4D research requires a more acute se...

Caste, Class, and Race : A Study in Social Dynamics

Abstract: A 1948 sociological analysis of the issues of caste, class, and race relations in the United States and the world.

Individual-level cultural consumer engagement styles: Conceptualization, propositions and implications

Abstract: While the consumer engagement (CE) concept is gaining traction in the literature, little remains known regarding the ways in which consumers displaying differing cultural traits engage with brands and their differences The purpose of this paper is to explore CE with brands for consumers exhibiting differing cultural traits, and develop a set of research propositions for these individuals’ cognitive, emotional, behavioral, and social CE in brand interactions These propositions, collectively, reflect consumers’ individual-level cultural CE styles – consumers’ motivationally driven disposition to think, feel, act, and relate to others in a certain manner characteristic of their specific individual cultural traits in brand interactions,In this conceptual paper, literature is reviewed in the areas of CE and its conceptual relationship with Yoo et al’s (2011) individual cultural values,Key differences between individual-level cultural traits and consumers’ ensuing cognitive, emotional, behavioral, and social CE with brands are addressed in a set of research propositions based on Yoo et al’s model of individual cultural values, from which the concept of individual-level cultural CE styles is developed,This research explores differences across individuals displaying differing cultural traits and their ensuing CE with brands, which remains underexplored to date It also develops the concept of individual-level cultural CE styles, which reflect consumers’ characteristic cultural trait-based cognitions, emotions, behaviors, and social dynamics in engaging with particular brands,The outlined managerial implications reveal that unique marketing approaches are expected to be effective for engaging consumers exhibiting different cultural traits with brands, based on their distinctive CE styles (eg focusing on personalized interactions/interactions that stress consumers’ similarity to and fit with salient others for individualist/collectivist consumers, respectively),This paper makes two important theoretical contributions First, by offering a conceptual analysis of consumers displaying differing cultural traits and their ensuing engagement with brands, it provides an early attempt to explore individual-level cultural CE-based differences Second, it develops the concept of individual-level cultural CE styles, which is expected to hold important theoretical and managerial implications

Reflections on the Role of University to Face the Challenges of Knowledge Society for the Local Economic Development

Abstract: This paper proposes an analysis of the evolution of approaches to knowledge management in order to identify useful patterns and perspectives for the improvement of efficiency, effectiveness, and affordable of managerial models for the economic development. The contribution offered by the literature is analyzed in the social network theory perspective and is reinterpreted in the light of the viable system approach (vSa) as a meta-model useful to highlight variables and processes involved in the interactions among several actors. The systematization of the contributions on the knowledge management facilitates the reading and the understanding of dominant managerial models, and somehow, outlines traits and characteristics of the knowledge society—as construct based on the relationship—that traditional approaches and instruments are often not properly adequate to understand. In this perspective, the paper aims to investigate the possible and potential contribution that university can offer to address the behaviors of local actors toward pathways of knowledge co-creation, able to positively impact on the local economic and social dynamics, in a win-win logic framework. Using a cross disciplinary approach, the paper proposes a conceptual framework able to identify possible influences that university can enforce on the local context in order to improve the social alignment requested to evolve from a transactional to a relational perspective, in which all actors play an active role in the processes of value generation and their needs are effectively satisfied. Proposed reflections are supported by the analysis of some practical observations with reference to the territory of Puglia region in Italy. They highlight the relevance of university as a key actor able to address the local resources to face the challenge of a changeable emerging context.

Knowledge politics in participatory climate change adaptation research on agroecology in Malawi

Abstract: Climate change is projected to have severe implications for smallholder agriculture in Africa, with increased temperatures, increased drought and flooding occurrence, and increased rainfall variability. Given these projections, there is a need to identify effective strategies to help rural communities adapt to climatic risks. Yet, relatively little research has examined the politics and social dynamics around knowledge and sources of information about climate-change adaptation with smallholder farming communities. This paper uses a political ecology approach to historically situate rural people's experiences with a changing climate. Using the concept of the co-production of knowledge, we examine how Malawian smallholder farmers learn, perceive, share and apply knowledge about a changing climate, and what sources they draw on for agroecological methods in this context. As well, we pay particular attention to agricultural knowledge flows within and between households. We ask two main questions: Whose knowledge counts in relation to climate-change adaptation? What are the political, social and environmental implications of these knowledge dynamics? We draw upon a long-term action research project on climate-change adaptation that involved focus groups, interviews, observations, surveys, and participatory agroecology experiments with 425 farmers. Our findings are consistent with other studies, which found that agricultural knowledge sources were shaped by gender and other social inequalities, with women more reliant on informal networks than men. Farmers initially ranked extension services as important sources of knowledge about farming and climate change. After farmers carried out participatory agroecological research, they ranked their own observation and informal farmer networks as more important sources of knowledge. Contradictory ideas about climate-change adaptation, linked to various positions of power, gaps of knowledge and social inequalities make it challenging for farmers to know how to act despite observing changes in rainfall. Participatory agroecological approaches influenced adaptation strategies used by smallholder farmers in Malawi, but most still maintained the dominant narrative about climate-change causes, which focused on local deforestation by rural communities. Smallholder farmers in Malawi are responsible for <1% of global greenhouse gas emissions, yet our results show that the farmers often blame their own rural communities for changes in deforestation and rainfall patterns. Researchers need to consider differences knowledge and power between scientists and farmers and the contradictory narratives at work in communities to foster long-term change.

Detecting leadership in peer-moderated online collaborative learning through text mining and social network analysis

Abstract: Structured tasks and peer-moderated discussions are pedagogical models that have shown unique benefits for online collaborative learning. Students appointed with leadership roles are able to positively affect the dynamics in their groups by engaging with participants, raising questions, and advancing problem solving. To help monitoring and controlling the latent social dynamics associated with leadership behavior, we propose a methodological approach that makes use of computational techniques to mine the content of online communications and analyze group structure to identify students who behave as leaders. Through text mining and social network analysis, we systematically process the discussion posts made by students from four sections of an online course in an American university. The results allow us to quantify each individual's contribution and summarize their engagement in the form of a leadership index. The proposed methodology, when compared to judgements made by experts who manually coded samples of the data, is shown to have comparable performances, but, being fully automated, has the potential to be easily replicable. The summary offered by the leadership index is intended as actionable information that can guide just-in-time interventions together with other tools based on learning analytics.

Analytical sociology and computational social science.

Abstract: Analytical sociology focuses on social interactions among individuals and the hard-to-predict aggregate outcomes they bring about. It seeks to identify generalizable mechanisms giving rise to emerg ...

Combining role-play with interactive simulation to motivate informed climate action: Evidence from the World Climate simulation.

Abstract: Climate change communication efforts grounded in the information deficit model have largely failed to close the gap between scientific and public understanding of the risks posed by climate change. In response, simulations have been proposed to enable people to learn for themselves about this complex and politically charged topic. Here we assess the impact of a widely-used simulation, World Climate, which combines a socially and emotionally engaging role-play with interactive exploration of climate change science through the C-ROADS climate simulation model. Participants take on the roles of delegates to the UN climate negotiations and are challenged to create an agreement that meets international climate goals. Their decisions are entered into C-ROADS, which provides immediate feedback about expected global climate impacts, enabling them to learn about climate change while experiencing the social dynamics of negotiations. We assess the impact of World Climate by analyzing pre- and post-survey results from >2,000 participants in 39 sessions in eight nations. We find statistically significant gains in three areas: (i) knowledge of climate change causes, dynamics and impacts; (ii) affective engagement including greater feelings of urgency and hope; and (iii) a desire to learn and do more about climate change. Contrary to the deficit model, gains in urgency were associated with gains in participants’ desire to learn more and intent to act, while gains in climate knowledge were not. Gains were just as strong among American participants who oppose government regulation of free markets–a political ideology that has been linked to climate change denial in the US–suggesting the simulation’s potential to reach across political divides. The results indicate that World Climate offers a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science.

Complexity and Sustainability in Management: Insights from a Systems Perspective

Abstract: The growing inadequacy of traditional ‘management toolkits’ for dealing with ever more complex phenomena highlights the need for a rethinking of consolidated management approaches: it is necessary a paradigmatic change for setting a pathway of knowledge and taking into account awareness of the limits and, at the same time, capability of overcoming and updating past schema. Acknowledging the unquestionable value of the long tradition of systems thinking contributions to social sciences and business management, the purpose of this work is to highlight the reasons why a systems approach is really needed to better understand business and social dynamics in condition of complexity, how the Viable Systems Approach can support decision making in condition of complexity, and how the discussion of complexity and the survival of viable systems in a complex scenario, implies inevitably, discussion about sustainability.

Incorporating Social System Dynamics in the Columbia River Basin: Food-Energy-Water Resilience and Sustainability Modeling in the Yakima River Basin

Abstract: In the face of climate change, achieving resilience of desirable aspects of food-energy-water (FEW) systems already strained by competing multi-scalar social objectives requires interdisciplinary approaches. This study is part of a larger effort exploring “Innovations in the Food-Energy-Water Nexus (INFEWS)” in the Columbia River Basin (CRB) through coordinated modeling and simulated management scenarios. Here, we focus on a case study and conceptual mapping of the Yakima River Basin (YRB), a sub-basin of the CRB. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic and governance systems); however, more attention to social drivers and outcomes is needed. Our goals are to identify several underutilized ways to incorporate social science perspectives into FEW nexus research and to explore how this interdisciplinary endeavor alters how we assess innovations and resilience in FEW systems. First, we investigate insights on FEW nexus resilience from the social sciences. Next, we delineate strategies for further incorporation of social considerations into FEW nexus research, including the use of social science perspectives and frameworks such as socio-ecological resilience and community capitals. Then, we examine a case study of the YRB, focusing on the historical development of the FEW nexus and innovations. We find that a resilience focus applied to the FEW nexus can inadvertently emphasize a status quo imposed by those already in power. Incorporating perspectives from the social sciences, which highlight issues related to inequality, power, and social justice, can address these shortcomings and inform future innovations. Finally, we use causal loop diagrams to explore the role of the social in the FEW nexus, and we suggest ways to incorporate social aspects into an existing stock and flow object-oriented modeling system. This project represents a starting point for a continued research agenda that incorporates social dynamics into FEW system resilience modeling and management in the CRB.

Opinion formation on dynamic networks: identifying conditions for the emergence of partisan echo chambers.

Abstract: Modern political interaction is characterized by strong partisanship and a lack of interest in information sharing and agreement across party lines. It remains largely unclear how such partisan echo chambers arise and how they coevolve with opinion formation. Here, we explore the emergence of these structures through the lens of coevolutionary games. In our model, the payoff of an individual is determined jointly by the magnitude of their opinion, their degree of conformity with their social neighbours and the benefit of having social connections. Each individual can simultaneously adjust their opinion and the weights of their social connections. We present and validate the conditions for the emergence of partisan echo chambers, characterizing the transition from cohesive communities with a consensus to divisive networks with splitting opinions. Moreover, we apply our model to voting records of the US House of Representatives over a timespan of decades to understand the influence of underlying psychological and social factors on increasing partisanship in recent years. Our work helps elucidate how the division of today has come to be and how cohesion and unity could otherwise be attained on a variety of political and social issues.

Linking the fine-scale social environment to mating decisions: a future direction for the study of extra-pair paternity.

Abstract: Variation in extra-pair paternity (EPP) among individuals of the same population could result from stochastic demography or from individual differences in mating strategies. Although the adaptive value of EPP has been widely studied, much less is known about the characteristics of the social environment that drive the observed patterns of EPP. Here, we demonstrate how concepts and well-developed tools for the study of social behaviour (such as social network analysis) can enhance the study of extra-pair mating decisions (focussing in particular on avian mating systems). We present several hypotheses that describe how characteristics of the social environment in which individuals are embedded might influence the levels of EPP in a socially monogamous population. We use a multi-level social approach (Hinde, 1976) to achieve a detailed description of the social structure and social dynamics of individuals in a group. We propose that the pair-bond, the direct (local) social environment and the indirect (extended) social environment, can contribute in different ways to the variation observed in the patterns of EPP, at both the individual and the population level. A strength of this approach is that it integrates into the analysis (indirect) interactions with all potential mates in a population, thus extending the current framework to study extra-pair mating behaviour. We also encourage the application of social network methods such as temporal dynamic analysis to depict temporal changes in the patterns of interactions among individuals in a group, and to study how this affects mating behaviour. We argue that this new framework will contribute to a better understanding of the proximate mechanisms that drive variation in EPP within populations in socially monogamous species, and might ultimately provide insights into the evolution and maintenance of mating systems.

Inspiring a broader socio-hydrological negotiation approach with interdisciplinary field-based experience

Abstract: Socio‐hydrology advanced the field of hydrology by considering humans and their activities as part of the water cycle, rather than as external drivers. Models are used to infer reproducible trends in human interactions with water resources. However, defining and handling water problems in this way may restrict the scope of such modeling approaches. We propose an interdisciplinary socio‐hydrological approach to overcome this limit and complement modeling approaches. It starts from concrete field‐based situations, combines disciplinary as well as local knowledge on water‐society relationships, with the aim of broadening the hydro‐centric analysis and modeling of water systems. The paper argues that an analysis of social dynamics linked to water is highly complementary to traditional hydrological tools but requires a negotiated and contextualized interdisciplinary approach to the representation and analysis of socio‐hydro systems. This reflection emerged from experience gained in the field where a water‐budget modeling framework failed to adequately incorporate the multiplicity of (non‐hydrological) factors that determine the volumes of withdrawals for irrigation. The pathway subsequently explored was to move away from the hydrologic view of the phenomena and, in collaboration with social scientists, to produce a shared conceptualization of a coupled human‐water system through a negotiated approach. This approach changed the way hydrological research issues were addressed and limited the number of strong assumptions needed for simplification in modeling. The proposed socio‐hydrological approach led to a deeper understanding of the mechanisms behind local water‐related problems and to debates on the interactions between social and political decisions and the dynamics of these problems.

Social Solidarity, Collective Identity, Resilient Communities: Two Case Studies from the Rural U.S. and Uruguay

Abstract: Worldwide, communities face disruptions driven by phenomena such as climate change and globalization. Socio-ecological resilience theorists have called for greater attention to the social dynamics that inform whether and how communities are reorganized and sustained in response to such challenges. Scholars increasingly stress that social heterogeneities provide resources that communities can mobilize to adapt and sustain themselves in response to disruptions. Utilizing the sociological literature that emphasizes that social solidarities and collective identities are centrally important to community responses to socio-ecological disruptions, we argue that solidarities grounded in collective identities can act as important mediators between social heterogeneity and resilience. Drawing on qualitative data from rural communities in the central United States and southwestern Uruguay, we explore how group solidarity enabled individuals to more effectively draw on their diverse knowledges, skills, and resources to sustain their communities. Linked by a collective identity grounded in rurality, in each setting, individuals effectively worked together to adapt to emerging socio-ecological disruptions. These results suggest that we can better understand how social heterogeneities inform resilience by considering how solidarities grounded in collective identities influence whether and how individuals can successfully cooperate to rearrange and sustain their communities. When working with rural communities, specifically, it will be especially important to account for solidarities and collective identities tied to rurality.

The PInSoRo dataset: Supporting the data-driven study of child-child and child-robot social dynamics.

Abstract: The study of the fine-grained social dynamics between children is a methodological challenge, yet a good understanding of how social interaction between children unfolds is important not only to Developmental and Social Psychology, but recently has become relevant to the neighbouring field of Human-Robot Interaction (HRI). Indeed, child-robot interactions are increasingly being explored in domains which require longer-term interactions, such as healthcare and education. For a robot to behave in an appropriate manner over longer time scales, its behaviours have to be contingent and meaningful to the unfolding relationship. Recognising, interpreting and generating sustained and engaging social behaviours is as such an important—and essentially, open—research question. We believe that the recent progress of machine learning opens new opportunities in terms of both analysis and synthesis of complex social dynamics. To support these approaches, we introduce in this article a novel, open dataset of child social interactions, designed with data-driven research methodologies in mind. Our data acquisition methodology relies on an engaging, methodologically sound, but purposefully underspecified free-play interaction. By doing so, we capture a rich set of behavioural patterns occurring in natural social interactions between children. The resulting dataset, called the PInSoRo dataset, comprises 45+ hours of hand-coded recordings of social interactions between 45 child-child pairs and 30 child-robot pairs. In addition to annotations of social constructs, the dataset includes fully calibrated video recordings, 3D recordings of the faces, skeletal informations, full audio recordings, as well as game interactions.

Interactions between social learning and technological learning in electric vehicle futures

Abstract: The transition to electric vehicles is an important strategy for reducing greenhouse gas emissions from passenger cars. Modelling future pathways helps identify critical drivers and uncertainties. Global integrated assessment models (IAMs) have been used extensively to analyse climate mitigation policy. IAMs emphasise technological change processes but are largely silent on important social and behavioural dimensions to future technological transitions. Here, we develop a novel conceptual framing and empirical evidence base on social learning processes relevant for vehicle adoption. We then implement this formulation of social learning in IMAGE, a widely-used global IAM. We apply this new modelling approach to analyse how technological learning and social learning interact to influence electric vehicle transition dynamics. We find that technological learning and social learning processes can be mutually reinforcing. Increased electric vehicle market shares can induce technological learning which reduces technology costs while social learning stimulates diffusion from early adopters to more risk-averse adopter groups. In this way, both types of learning process interact to stimulate each other. In the absence of social learning, however, the perceived risks of electric vehicle adoption among later-adopting groups remains prohibitively high. In the absence of technological learning, electric vehicles remain relatively expensive and therefore is only an attractive choice for early adopters. This first-of-its-kind model formulation of both social and technological learning is a significant contribution to improving the behavioural realism of global IAMs. Applying this new modelling approach emphasises the importance of market heterogeneity, real-world consumer decision-making, and social dynamics as well as technology parameters, to understand climate mitigation potentials.

A Social-Ecological Approach to Addressing Emotional and Behavioral Problems in Schools: Focusing on Group Processes and Social Dynamics.

Abstract: A substantial body of evidence verifies that social-emotional learning (SEL) can be effectively taught in schools and can reduce the prevalence and impact of emotional and behavioral problems (EBP)...

The social dynamics of turbine tourism and recreation: Introducing a mixed-method approach to the study of the first U.S. offshore wind farm

Abstract: Understanding the complex dynamics that influence energy transitions requires mixed methods and collaborations among researchers, resource managers, and communities. This essay details how an interdisciplinary team of researchers used a mixed-method approach to study the social dimensions of tourism and recreation as they relate to the first offshore wind farm in the United States, the Block Island Wind Farm. Although impacts to tourism from wind energy systems are widely cited as a concern by communities and policymakers, little work has sought to define what constitutes tourism and recreation impacts or provided empirical evidence of impacts from operating projects. Researchers adopted an iterative approach to research that combined discrete studies using media content analysis, ethnographic participant observation, and stakeholder focus groups, to understand the social effects of the wind farm on the tourism and recreation experience and the quality of life in Block Island and coastal Rhode Island. We detail key insights from our experimentation with an iterative mixed-method approach at Block Island and offer lessons for future studies using collaborative approaches to understand both the tangible and the intangible social dynamics of energy system transitions.

Model-Driven Information Security Risk Assessment of Socio-Technical Systems

Abstract: As more aspects of life transition to the digital domain, computer systems become increasingly complex but also more social. But assessing a socio-technical system is no trivial task: it often requires intimate knowledge of the system, awareness of the social dynamics and trust relationships of its users, a deep understanding of both hardware and software, as well as the ability to quantify risks, communicate security policies and engage stakeholders. Conceptual models, as tools designed to help make sense of complex issues, can help with some of these problems. This dissertation explores the role of conceptual models in assessing risks related to the development and operation of socio-technical systems. I propose several model-driven modelling and analysis approaches which can be used stand-alone but can also augment existing risk management processes. The approaches are centered on three modelling paradigms not traditionally used in risk management. I use Tangible modelling, i.e. “physical” modeling using graspable three-dimensional tokens, to facilitate the collaborative modelling of socio-technical systems. I find it has beneficial effects on the quality of the resulting models when the modellers, especially when some of the modelers have a technical background. I use argumentation modelling, i.e. recording the rationale behind claims can support the security decision-making process, to support the security decision-making process. I find that structuring the risk assessment as a set of arguments forces risk assessors to make their assumptions explicit and that maintaining a mapping between risks and countermeasures increases the defensibility of the resulting security requirements. I use value modelling, i.e. understanding the value transfers which underpin any commercial information system, to quantify risks, identify vulnerabilities to fraud, and rationalize processes. I propose an ontological and procedural extension to automate this process.

Frustrated sovereigns: the agency that makes the world go around

Abstract: In this article, the introduction to this Special Issue, we underline the importance of the dynamics of misrecognition for the study of world politics. We make the case for shifting the focus from ‘recognition’, where it has long been cast in social, political and, more recently, International Relations theory, to misrecognition. We do so by returning to the original theorisation of misrecognition, Hegel’s dialectic of the master and servant. Our point of departure is not only that the desire for recognition is key social dynamic, but that the failure to obtain this recognition is built into this very desire. It is a crucial factor for understanding how international actors behave, including, but not only, states.Thus understood, the desire for recognition is not simply a desire for social goods, for status or for statehood, but for more agency – more capacity to act. We explore the logic of misrecognition and show how the international system is a symbolic structure that is ordained by an unrealisable ideal of what we call ‘sovereign agency’.

Ethnographic understandings of ethnically diverse neighbourhoods to inform urban design practice

Abstract: The aim of this paper is to inform urban design practice through deeper understanding and analysis of the social dynamics of public outdoor space in ethnically diverse neighbourhoods. We hypothesis...

The ecosystem of commons-based peer production and its transformative dynamics:

Abstract: This essay discusses peer-to-peer social dynamics and the relevant technological infrastructures that enable new modes of production. Commons-based peer production is presented as an alternative to...