Archive for the ‘Social network’ Category
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.
Over the past thirty years, a new systemic conception of life has emerged at the forefront of science. New emphasis has been given to complexity, networks, and patterns of organisation leading to a novel kind of ‘systemic’ thinking. This volume integrates the ideas, models, and theories underlying the systems view of life into a single coherent framework. Taking a broad sweep through history and across scientific disciplines, the authors examine the appearance of key concepts such as autopoiesis, dissipative structures, social networks, and a systemic understanding of evolution. The implications of the systems view of life for health care, management, and our global ecological and economic crises are also discussed. Written primarily for undergraduates, it is also essential reading for graduate students and researchers interested in understanding the new systemic conception of life and its implications for a broad range of professions – from economics and politics to medicine, psychology and law.
Cooperation phenomena are ubiquitous in social systems. In this paper, based on the Prisoner’s dilemma game model, we study the evolution of cooperation in two social networks, namely, the scientific collaboration network (SCN) and the “Pretty-Good-Privacy” (PGP) trust network. Our investigation shows that due to the existence of community structures in real social networks, small-degree individuals tend to follow their local hubs’ behavior and would adopt their strategies in the long run. Hence, the community structure promotes the emergence of persistence behavior. This provides a clue to understanding the evolution of cooperation in social systems.
Contemporary definitions of leadership advance a view of the phenomenon as relational, situated in specific social contexts, involving patterned emergent processes, and encompassing both formal and informal influence. Paralleling these views is a growing interest in leveraging social network approaches to study leadership. Social network approaches provide a set of theories and methods with which to articulate and investigate, with greater precision and rigor, the wide variety of relational perspectives implied by contemporary leadership theories. Our goal is to advance this domain through an integrative conceptual review. We begin by answering the question of why–Why adopt a network approach to study leadership? Then, we offer a framework for organizing prior research. Our review reveals 3 areas of research, which we term: (a) leadership in networks, (b) leadership as networks, and (c) leadership in and as networks. By clarifying the conceptual underpinnings, key findings, and themes within each area, this review serves as a foundation for future inquiry that capitalizes on, and programmatically builds upon, the insights of prior work. Our final contribution is to advance an agenda for future research that harnesses the confluent ideas at the intersection of leadership in and as networks. Leadership in and as networks represents a paradigm shift in leadership research–from an emphasis on the static traits and behaviors of formal leaders whose actions are contingent upon situational constraints, toward an emphasis on the complex and patterned relational processes that interact with the embedding social context to jointly constitute leadership emergence and effectiveness.
The concept of shared knowledge structures is introduced as one way of demonstrating how personal relationships serve as a bridge between collective activity at the level of the social network and cognitive activity at the level of the individual. The field of social cognition has studied how individuals organize information, and social network analysis has studied how information is passed within groups, but both have largely ignored the role that personal relationships play in leading individuals to share the ways they organize and interpret this information. This conceptual framework is applied to two qualitative studies on the production of shared knowledge structures: first, for knowledge about coping with the stresses of recent widowhood, and second, for the organization of knowledge about preventing heart attacks. The results point to the importance of integrating work on social cognition, personal relationships, and social networks.
Many people see peer-to-peer platforms as game-changers in the world of work with the potential of reinventing the economy and giving individuals the power of the corporation. Others are sceptical and warn that the new architectures of participation and choice are in reality architectures of exploitation, giving rise to a new class of workers, “the precariat”, people who endure insecure conditions, very short-term work and low wages with no collective bargaining power, abandoned by the employee unions, rendering them atomized and powerless. In creative, knowledge-based work it is increasingly difficult to know the best mix of capabilities and tasks in advance. What if the organization really should be a process of emergent self-organizing in the way the platforms make possible? Instead of thinking about the organization let’s think about organizing as an ongoing thing. Then the managerial task is to make possible very easy and very fast emergent responsive interaction and group formation. The principles behind these trends are crucially important for the future of firms and society. A platform (company) should therefore be as open, as accessible and as supportive as possible to as many users as possible.
Read also: Peers Inc
Creating communities and societies that are ecologically sustainable is the great challenge of our time. What is sustained in a sustainable community is not economic growth, development, market share, or competitive advantage, but the entire web of life on which our long-term survival depends. We do not need to start from zero to design these communities, but can model them on nature’s ecosystems, which are sustainable communities of plants, animals, and microorganisms. Since the outstanding characteristic of the biosphere is its inherent ability to sustain life, a sustainable community is one that is designed in such a way that its ways of life, businesses, economy, physical structures, and technologies honor, support, and cooperate with nature’s inherent ability to sustain life.
What is the place of learning in sustainable communities? How can such learning be organized and facilitated? What are some underlying principles? These are some of the key questions that this book seeks to address from the perspective of social learning. Both ecological communities and human communities derive their essential properties, and in fact their very existence, from their relationships. Sustainability is not an individual property, but the property of an entire network. The important concept of feedback, which was discovered in cybernetics in the 1940s, is intimately connected with the network pattern. Because of feedback in living networks, these systems are capable of self-regulation and self-organization. A community can learn from its mistakes, because the mistakes travel and come back along these feedback loops. Next time around we can act differently. This means that a community has its own intelligence, its own learning capability. In fact, a living community is always a learning community.
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.
A key property of modern cities is increasing returns to scale—the finding that many socioeconomic outputs increase more rapidly than their population size. Recent theoretical work proposes that this phenomenon is the result of general network effects typical of human social networks embedded in space and, thus, is not necessarily limited to modern settlements. We examine the extent to which increasing returns are apparent in archaeological settlement data from the pre-Hispanic Basin of Mexico. We review previous work on the quantitative relationship between population size and average settled area in this society and then present a general analysis of their patterns of monument construction and house sizes. Estimated scaling parameter values and residual statistics support the hypothesis that increasing returns to scale characterized various forms of socioeconomic production available in the archaeological record and are found to be consistent with key expectations from settlement scaling theory. As a consequence, these results provide evidence that the essential processes that lead to increasing returns in contemporary cities may have characterized human settlements throughout history, and demonstrate that increasing returns do not require modern forms of political or economic organization.
Read also: Scaling Laws of Human Interaction Activity
Even though people in our contemporary technological society are depending on communication, our understanding of the underlying laws of human communicational behavior continues to be poorly understood. Here we investigate the communication patterns in 2 social Internet communities in search of statistical laws in human interaction activity. This research reveals that human communication networks dynamically follow scaling laws that may also explain the observed trends in economic growth. Speciﬁcally, we identify a generalized version of Gibrat’s law of social activity expressed as a scaling law between the ﬂuctuations in the number of messages sent by members and their level of activity. Gibrat’s law has been essential in understanding economic growth patterns, yet without an underlying general principle for its origin. We attribute this scaling law to long-term correlation patterns in human activity, which surprisingly span from days to the entire period of the available data of more than 1 year. Further, we provide a mathematical framework that relates the generalized version of Gibrat’s law to the long-term correlated dynamics, which suggests that the same underlying mechanism could be the source of Gibrat’s law in economics, ranging from large ﬁrms, research and development expenditures, gross domestic product of countries, to city population growth. These ﬁndings are also of importance for designing communication networks and for the understanding of the dynamics of social systems in which communication plays a role, such as economic markets and political systems.