Archive for the ‘Networks’ Category
During the last three or four decades labour, union, research and advocacy networks have interacted with networks of anti-capitalist or alter-globalist social justice activists. These interactions have enabled the (self-)organisation of working people across production networks linking the Global North and South. Especially after the crisis erupted in 2007-8, the process has expanded to include networks of self-employed, unemployed, marginalized and increasingly radicalised knowledge and service workers. Online social networks such as Facebook, Twitter, and Google Plus, but also free, ‘libre’ and open source software (FLOSS), offer new experiences complementary to traditional forms of organization. This Appendix presents a concise overview of networks constituted around the quest for ‘associated social relations of production’, or ‘peer production communities’. Whether labelled hackers, makers, diggers, guerrilla translators and so forth, and involving FLOSS and hardware production, collaborative digital, creative, artistic, media, graphic, and architecture projects, or Do-it-Yourself (DIY) or Do-it-with-Others (DIWO) practices, these networks connect highly educated individual knowledge, information, education and service workers.
Over the past decade there has been a growing public fascination with the complex connectedness of modern society. This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.
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This article contributes to an ongoing theoretical effort to extend the insights of relational and network sociology into adjacent domains. We integrate Simmel’s late theory of the relational self into the formal analysis of social relations, generating a framework for theorizing forms of association among self-relating individuals. On this model, every “node” in an interaction has relations not only to others but also to itself, specifically between its ideality and its actuality. We go on to integrate this self-relation into a formal model of social relations. This model provides a way to describe configurations of social interactions defined by the forms according to which social relations realize participants’ ideal selves. We examine four formal dimensions along which these self-relational relationships can vary: distance, symmetry, scope, and actualization.
“The ‘arborescenť model of thought designates the epistemplogy that informs all of Western thought, from botany to information sciences to theology”. Arbolic thought is a model to describe a system that is hierarchical, centered around a core belief, reductivistic, increasingly specialized, non-cyclical, linear, and ripe with segmentation and striation. Similar to a tree-like description of biological evolution or genealogy, arborescent systems start from a central origin and continue to evolve by branching into successively specialized generations. Vertical in nature, the arbolic is ordered, structured and “scientific”: it has a distinct train of thought, a clear inheritance, an order.
In contrast, the rhizome is brought forward as a matted web of interlinked concepts. Inspired by the wandering, non-centered root systems of grasses and plants, the rhizome appears non-linear, horizontal, nomadic, deterritorialized and heterogeneous. The rhizome cuts across and between the order of vertical space, connecting multiple points simultaneously in a network of nodes. Connected to each other at arbitrary points, the rhizomatic system is more concerned with the multiplicitous interlinking of concept, action and being.
Although it lacks a central dogma of a trunk/brain, it is a horizontal, bottom-up system that produces an emergent system of metabehavior that is strong, robust, and intelligent… in the non-standard sense of the word. Within nature, rhizomatic systems like ants or grassy weeds eventually win: “True, the weed produced no lilies, no battleships, no Sermons on the Mount… Eventually the weed gets the upper hand… The lily is beautiful, the cabbage is provender, the poppy is maddening – but the weed is rank growth… it points a moral.”
If intelligence could exist without a central brain, the rhizome would be it.
MMOGs (Massive Multiplayer Online Games) and MMORPGs (Massive Multiplayer Online Role-Playing Games) are considered to be complex, ever increasing systems with a full range of social and material practices, where true mastery of the game can only be achieved by working collaboratively with other players. In situated learning theory, it is argued that learning, thinking and knowing emerge from a world that is socially constructed. Just as in a real world community, when newcomers enter a MMOG, they are gradually introduced to a complex social framework through the tutelage of other community member. They learn to make sense of new areas, especially by engaging with others, discussing, reflecting, and sharing. In order for players to succeed in these games, they have to self-organize and collaborate in order to form guilds; constantly improve to remain competitive, visioning the enemy’s and guild’s reaction. Nevertheless, these are important leadership skills for the real world as well, revealing multiple similarities that link the gaming world and the real world. In this sense, it is imperative to understand how these virtual environments can develop or enhance skills that are important for a person’s life and work in the 21st century. This realization stresses the need for researching and analyzing the social structures that players create through their interactions with other players. However, despite the significant amount of educational research and the growing interest of the scientific community in MMOGs, there is a lack of empirical research considering cognitive and social aspects of these games. This paper outlines the theoretical rationale behind a doctoral research project currently in progress, which examines the leadership skills that can be developed in a self-organized community in MMOGs. In order to address these issues, this paper presents a theoretical framework for analyzing the social interactions in Multiplayer Serious Games, within the context of community of practice, activity theory, connectivism, self-organization and autopoietic theory.
In most social, information, and collaboration systems the complex activity of agents generates rapidly evolving time-varying networks. Temporal changes in the network structure and the dynamical processes occurring on its fabric are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset describing the activity of millions of individuals and investigate the temporal evolution of their egocentric networks. We empirically observe a simple statistical law characterizing the memory of agents that quantitatively signals how much interactions are more likely to happen again on already established connections. We encode the observed dynamics in a reinforcement process defining a generative computational network model with time-varying connectivity patterns. This activity-driven network model spontaneously generates the basic dynamic process for the differentiation between strong and weak ties. The model is used to study the effect of time-varying heterogeneous interactions on the spreading of information on social networks. We observe that the presence of strong ties may severely inhibit the large scale spreading of information by confining the process among agents with recurrent communication patterns. Our results provide the counter-intuitive evidence that strong ties may have a negative role in the spreading of information across networks.