Posts Tagged ‘social networks’
This report offers a framework with a set of concepts, hypotheses and methods that help with understanding collective action and intelligence in emergent network social movements. In connection to the rise of network-movements and as a reflection of the exhaustion of the traditional forms representative democracy, there have been a number of experiments and prototypes of new forms of democracy. D-CENT has produced theoretical analysis, data-analysis and data-visualisation of the appropriation by the network movements of a broad array of digital platforms and technologies used for political action, which generated huge processes of collective, citizen self-organisation.
In complex social systems such as those of many mammals, including humans, groups (and hence ego-centric social networks) are commonly structured in discrete layers. We describe a computational model for the development of social relationships based on agents’ strategies for social interaction that favour more less-intense, or fewer more-intense partners. A trust-related process controls the formation and decay of relationships as a function of interaction frequency, the history of interaction, and the agents’ strategies. A good fit of the observed layers of human social networks was found across a range of model parameter settings. Social interaction strategies which favour interacting with existing strong ties or a time-variant strategy produced more observation-conformant results than strategies favouring more weak relationships. Strong-tie strategies spread in populations under a range of fitness conditions favouring wellbeing, whereas weak-tie strategies spread when fitness favours foraging for food. The implications for modelling the emergence of social relationships in complex structured social networks are discussed.
The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a nonlinear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multidimensional nature of these interactions has largely been ignored, mostly because of lack of data. Here, for the first time, we analyze a complete, multirelational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering, and fatter-tail degree distribution. We then explore how the interdependence of different network types determines the organization of the social system. In particular, we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach, we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.
Is cognition an exclusive property of the individual or can groups have a mind of their own? We explore this question from the perspective of complex adaptive systems. One of the principal insights from this line of work is that rules that govern behavior at one level of analysis (the individual) can cause qualitatively different behavior at higher levels (the group). We review a number of behavioral studies from our lab that demonstrate how groups of people interacting in real-time can self-organize into adaptive, problem-solving group structures. A number of principles are derived concerning the critical features of such “distributed” information processing systems. We suggest that while cognitive science has traditionally focused on the individual, cognitive processes may manifest at many levels including the emergent group-level behavior that results from the interaction of multiple agents and their environment.
We develop a new approach to the study of the dynamics of link utilization in complex networks using data of empirical social networks. Counter to the perspective that nodes have particular roles, we find roles change dramatically from day to day. “Local hubs” have a power law degree distribution over time, with no characteristic degree value. We further study the dynamics of local motif structure in time-dependent networks, and find recurrent patterns that might provide empirical evidence for cycles of social interaction. Our results imply a significant reinterpretation of the concept of node centrality and network local structure in complex networks, and among other conclusions suggest that interventions targeting hubs will have significantly less effect than previously thought.
Civic networks of community-based organizations face significant challenges in working together to combat issues facing their community (e.g., gang violence, sex trafficking). In our research, we examined how local organizations tried to build and maintain connectedness over time as a network to fight child sex trafficking. We sought to understand how technology supports the social processes of connectedness in this context. Based on our analysis of the field data from this case study, we identify three categories of activities for building and maintaining connectedness. We also find that while different technologies are suited towards supporting different aspects of connectedness, there may be gaps in how adequately social media tools support connectedness in civic networks.
The findings we present in this paper indicate that there is a critical need for low-cost, more group-centric technologies for maintaining connectedness between community-based organizations over an extended period of time. Our work offers a lens for better understanding a context of an informal civic network where such connectedness needs to be supported as a first step in designing such technologies. This lens can help guide how more group-centric ICTs can be leveraged to create connectedness in civic networks. In future work, we plan to explore design approaches to supporting the processes of awareness-raising in this community-based context.
This paper’s purpose is to review social capital as discussed in the literature, identify controversies and debates, consider some critical issues, and propose conceptual and research strategies in building a theory. I will argue that such a theory and the research enterprise must be based on the fundamental understanding that social capital is captured from embedded resources in social networks . Deviations from this understanding in conceptualization and measurement lead to confusion in analyzing causal mechanisms in the macro- and micro-processes. It is precisely these mechanisms and processes, essential for an interactive theory about structure and action, to which social capital promises to make contributions . By considering social capital as assets in networks, the paper will discuss some issues in conceptualizations, measurements, and causal mechanisms (the factors leading to inequality of social capital and the returns following investments in social capital) . A proposed model will follow . The paper will conclude by calling attention to the rise of a new form of social capital, cybernetworks, and briefly suggesting how research on this topic promises to make important contributions to the research enterprise .
Previous research has focused heavily on community communications as they occur in e.g.
communities of practice. Still, as indicated by the concept of networked individualism, contacts are becoming more networked in nature and group membership is transient. The research presented here yields to the call of Garton et al to move away from the study of communication taking place only in groups and to also investigate the potential of computer-mediated communication to support interaction in unbound and sparsely-knit social networks. As a consequence, in chapters 5 and 6, I’ve adopted a research method which takes the relationship between people as the basic unit of analysis. In conclusion, as work practice in Western economies is evolving towards knowledge work, and knowledge work rests heavily on knowledge sharing, the combination of networked individualism and knowledge sharing seems a relevant subject of study.
Innovation – the process of obtaining, understanding, applying, transforming, managing and transferring knowledge – is a result of human collaboration, but it has become an increasingly complex process, with a growing number of interacting parties involved. Lack of innovation is not necessarily caused by lack of technology or lack of will to innovate, but often by social and cultural forces that jeopardize the cognitive processes and prevent potential innovation. This book focuses on the rule of social capital in the process of innovation: the social networks and the norms; values and attitudes (such as trust) of the actors; social capital as both bonding and bridging links between actors; and social capital as a feature at all spatial levels, from the single inventor to the transnational corporation. Contributors from a wide variety of countries and disciplines explore the cultural framework of innovation through empirics, case studies and examination of conceptual and methodological dilemmas.
Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks, although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others’ positive experiences constitutes a positive experience for people.