Archive for the ‘Networks’ Category
Despite current ads and slogans, the world doesn’t change one person at a time. It changes as networks of relationships form among people who discover they share a common cause and vision of what’s possible.This is good news for those of us intent on changing the world and creating a positive future. Rather than worry about critical mass, our work is to foster critical connections. We don’t need to convince large numbers of people to change; instead, we need to connect with kindred spirits. Through these relationships, we will develop the new knowledge, practices, courage, and commitment that lead to broad-based change. But networks aren’t the whole story. As networks grow and transform into active, working communities of practice, we discover how life truly changes, which is through emergence. When separate, local efforts connect with each other as networks then strengthen as communities of practice, suddenly and surprisingly a new system emerges at a greater level of scale. This system of influence possesses qualities and capacities that were unknown in the individuals. It isn’t that they were hidden; they simply didn’t exist until the system emerges. They are properties of the system, not the individual, but once there, individuals possess them. And the system that emerges always possesses greater power and influence than is possible through planned, incremental change. Emergence is how life creates radical change and takes things to scale.
The primary hypothesis that I will endeavor to support is that leveraging the benefits of network organization constitutes a new source of power and a new way of accomplishing global governance. As individuals and groups engage each other globally, the locus of global governance shifts from state-centered activities to distributed networks. The cumulative effect of the shift from hierarchies to networks is a system of overlapping spheres of authority and regimes of collective action called “panarchy.”
Complexity + Networks + Connectivity => Panarchy
In this paper, I have shown that the convergence of processes crosses a critical threshold to create new possibilities for governance. The result is a new system. The key distinction between the old system and the new lies in the fact that governance in the old system was achieved through states, whereas in the new system it is not only achieved outside of hierarchies through horizontal networks, but is in fact often achieved in spite of hierarchies.
The study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and sociology. This book promotes the diverse nature of the study of complex networks by balancing the needs of students from very different backgrounds. It references the most commonly used concepts in network theory, provides examples of their applications in solving practical problems, and clear indications on how to analyse their results. In the first part of the book, students and researchers will discover the quantitative and analytical tools necessary to work with complex networks, including the most basic concepts in network and graph theory, linear and matrix algebra, as well as the physical concepts most frequently used for studying networks. They will also find instruction on some key skills such as how to proof analytic results and how to manipulate empirical network data. The bulk of the text is focused on instructing readers on the most useful tools for modern practitioners of network theory. These include degree distributions, random networks, network fragments, centrality measures, clusters and communities, communicability, and local and global properties of networks. The combination of theory, example and method that are presented in this text, should ready the student to conduct their own analysis of networks with confidence and allow teachers to select appropriate examples and problems to teach this subject in the classroom.
Networks and teams have become central in the way we organize ourselves inside and between organizations. With Kurt Lewin’s idea that there is nothing as useful as a good theory, it is remarkable that both the concept of networks and the concept of teams often are defined very implicit and seldom are used consistently. In this article I will address some of the reasons creating this situation. The main reason is that we in the western hemisphere is in the middle of something Peter Senge calls Galilean shifts, where our traditional worldview no longer is sufficient to explain phenomena like networks and teams. This means that teams become a central part of the everyday life of leaders and employees and the teams become crucial in order to make it possible for the individual to act in a sensible way in a situation where a good solution only can be found, if they’re able to bend or even overlook the bureaucratic rules and procedures that most organizations have. The teams become crucial in order to make it possible for the individual to act with large degrees of freedom and commitment in their everyday life. It is through the teams and the networks that the necessary information and training takes place. During the day most leaders and employees will move from one team to the next and solve the tasks that are necessary or possible right now.
Over the last decades, the idea that communication constitutes organizations (CCO) has been gaining considerable momentum in organization studies. The CCO perspective provides new insights into key organizational issues, such as the relation between stability and change, between micro-level and macro-level phenomena, or between emergence and control. However, despite various theoretical advancements, the CCO perspective’s range of methodologies is still limited to analyzing local communication episodes, rather than studying organizations as broader networks of communication episodes. In this paper, we present a new methodological approach to the study of the relation between organization and communication, based on network analysis. Following a discussion of existing network approaches, we incorporate the fundamental assumptions of the CCO perspective into a methodology that places communication at the center of network analysis by turning the prevalent network perspective inside out, so that the vertices of the network represent communication episodes and the edges represent individuals. We illustrate our methodology with an empirical case study, in which we examine the structures and dynamics of an actual organization as a network of communication episodes.
This paper reviews the general philosophy underlying the transdisciplinary research in the Evolution, Complexity and Cognition (ECCO) group. The ECCO conceptual framework is based on an ontology of action: the fundamental constituents of reality are seen as actions and the agents that produce them. More complex phenomena are conceived as self-organizing networks of interacting agents that evolve to become increasingly complex, adaptive and intelligent systems. The resulting worldview allows us to address the most fundamental issues of philosophy, including metaphysics, epistemology, ethics, futurology and praxeology. It in particular tackles the recurrent issues surrounding the matter-mind duality, including the origins of purposefulness and of subjective experience, and the relation between first-person and third-person perspectives. It achieves this by extending the intentional stance down to the simplest agents, elementary particles. This action-based view moreover supports a variety of practical applications, including the design of self-organizing technological systems, of systems that mobilize people to work in a motivated and coordinated manner, and of systems that support the collaborative development and dissemination of knowledge networks. The appendix of the paper, which is structured as a glossary, systematically defines and surveys the fundamental concepts of the ECCO framework.
Change is hard, especially in a large organization. Numerous studies have shown that employees tend instinctively to oppose change initiatives because they disrupt established power structures and ways of getting things done. However, some leaders do succeed—often spectacularly—at transforming their workplaces. What makes them able to exert this sort of influence when the vast majority can’t? All of our findings underscore the importance of networks in influencing change. First, formal authority may give you the illusion of power, but informal networks always matter, whether you are the boss or a middle manager. Second, think about what kind of network you have—or your appointed change agent has—and make sure it matches the type of change you’re after. A bridging network helps drive divergent change; a cohesive network is preferable for nondivergent change. Third, always identify and cultivate fence-sitters, but handle resisters on a case by case basis. We saw clear evidence that these three network factors dramatically improved managers’ odds of successfully implementing all kinds of reforms. We believe they can do the same for change agents in a wide variety of organizations.
Read also: The Secrets of Great Change Agents
Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has been so far devoted to the investigation of communities in real networks. We present a systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks. We find that the mesoscopic organization of networks of the same category is remarkably similar. This is reflected in several characteristics of community structure, which can be used as “fingerprints” of specific network categories. While community size distributions are always broad, certain categories of networks consist mainly of tree-like communities, while others have denser modules. Average path lengths within communities initially grow logarithmically with community size, but the growth saturates or slows down for communities larger than a characteristic size. This behaviour is related to the presence of hubs within communities, whose roles differ across categories. Also the community embeddedness of nodes, measured in terms of the fraction of links within their communities, has a characteristic distribution for each category. Our findings, verified by the use of two fundamentally different community detection methods, allow for a classification of real networks and pave the way to a realistic modelling of networks’ evolution.
Many real networks in nature and society share two generic properties: they are scale-free and they display a high degree of clustering. We show that these two features are the consequence of a hierarchical organization, implying that small groups of nodes organize in a hierarchical manner into increasingly large groups, while maintaining a scale-free topology. In hierarchical networks, the degree of clustering characterizing the different groups follows a strict scaling law, which can be used to identify the presence of a hierarchical organization in real networks. We ﬁnd that several real networks, such as the WorldWideWeb, actor network, the Internet at the domain level, and the semantic web obey this scaling law, indicating that hierarchy is a fundamental characteristic of many complex systems.