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book review of The Exploit: a Theory of Networks
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To understand what went wrong, let's look at three distinct ways that the term network is used in the literature. (See Milton Mueller's excellent book Networks and States for more on how the term is used in different ways.)
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In network analysis, a network is a set of nodes (units) connected by links or edges. Since this is a form of analysis, anything can be considered a node - an academic paper (linked via citations), a set of phones (linked by wires and switches), a group of people (linked by communication lines), you name it. As long as the units are consistent and the links are identifiable, you can perform a network analysis. That doesn't mean that the phenomenon you're studying is a network in an objective sense.
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"Go to any social gathering in your neighborhood and you will notice that people interact mostly with others who are similar in terms of age, gender, race, attributes, and behaviors. This tendency of people to have similar friends—known as homophily—is one of the most pervasive features of social networks (1). A key question is how much of the homophily in behavior can be attributed to social diffusion, that is, direct causal influence of one person on another through social ties (2, 3). Results from two clever Internet experiments reported by Centola last year (4) and on page 1269 of this issue (5) shed light on how the particular arrangement of social ties promotes social diffusion."
"The “performativity thesis” is the claim that parts of contemporary economics and finance, when carried out into the world by professionals and popularizers, reformat and reorganize the phenomena they purport to describe, in ways that bring the world into line with theory. Practical technologies, calculative devices and portable algorithms give actors tools to implement particular models of action. I argue that social network analysis is performative in the same sense as the cases studied in this literature. Social network analysis and finance theory are similar in key aspects of their development and effects. For the case of economics, evidence for weaker versions of the performativity thesis in quite good, and the strong formulation is circumstantially supported. Network theory easily meets the evidential threshold for the weaker versions; I offer empirical examples that support the strong (or “Barnesian”) formulation. Whether these parallels are a mark in favor of the thesis or a strike against it is an open question. I argue that the social network technologies and models now being “performed” build out systems of generalized reciprocity, connectivity, and commons-based production. This is in contrast both to an earlier network imagery that emphasized self-interest and entrepreneurial exploitation of structural opportunities, and to the model of action typically considered to be performed by economic technologies."
"We study several longstanding questions in media communications research, in the context of the microblogging service Twitter, regarding the production, flow, and consumption of information. To do so, we exploit a recently introduced feature of Twitter---known as Twitter lists---to distinguish between elite users, by which we mean specifically celebrities, bloggers, and representatives of media outlets and other formal organizations, and ordinary users. Based on this classification, we find a striking concentration of attention on Twitter---roughly 50% of tweets consumed are generated by just 20K elite users---where the media produces the most information, but celebrities are the most followed. We also find significant homophily within categories: celebrities listen to celebrities, while bloggers listen to bloggers etc; however, bloggers in general rebroadcast more information than the other categories. Next we re-examine the classical ``two-step flow'' theory of communications, finding considerable support for it on Twitter, but also some interesting differences. Third, we find that URLs broadcast by different categories of users or containing different types of content exhibit systematically different lifespans. And finally, we examine the attention paid by the different user categories to different news topics."
"This passage emphasizes quite a few themes that have been important throughout UnderstandingSociety -- the heterogeneity of social phenomena, the difficulty of formulating a clear understanding of social ontology, and the challenge of representing the processes of aggregation through which individual social actions contribute to mid- and large-scale social outcomes.
So how do the analytical resources of network theory contribute to a better understanding of the ways that actions aggregate into outcomes?"
David Alderson has become a leading advocate for formulating the foundations of network science so that its predictions can be applied to real networks. He is an assistant professor in the Operations Research Department at the Naval Postgraduate School in Monterey, Calif., where he conducts research with military officer-students on the operation, attack, and defense of network infrastructure systems. We interviewed him to find out what is going on.
We present a methodology to extract the backbone of complex networks in which the weight and direction of links, as well as non-topological state variables associated with nodes play a crucial role. This methodology can be applied in general to networks in which mass or energy is flowing along the links. In this paper, we show how the procedure enables us to address important questions in economics, namely how control and wealth is structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks in the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely lying in the hands of very few important shareholders. This result has previously not been reported, as it is not observable without the kind of network analysis developed here.
She observes – correctly, I think – that most strategic insight and initiative is limited by the fact of ego-centric networks: we know who we know, and only on a very limited basis do we indirectly know those whom our direct network knows.
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The other aspect that either she had no time to address last evening, or has not considered, is the vital importance of identity construction in the face of organization change. My research seems to indicate that Identity-valence may be the most significant impediment to change, which is one of the main reasons why I think many hierarchical restructurings tend to change nothing. It's also the reason I suggest that any real change that also changes the framework on which Identity-valence is constructed is exceedingly difficult and requires considerable effort, distraction, coaching, and dedication-to-the-cause to effect. I do think that it’s also consistent with people in Stephenson’s network roles (hub, gatekeeper, pulsetaker) retaining those network roles, since they are a large part of how people create their Identity-valence relationship with the organization (interestingly, both in ba- and fungible-forms as I think about it).
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What interests me, more than the non-egalitarian nature of such groups (especially hierarchies), are the power dynamics of groups that are purportedly equal. We have been conditioned by the multiple hierarchies in most of the groups we participate in (including families, workplaces, and recreational teams), to wait for 'leaders' to present themselves (or be assigned) in the groups we are part of. We tend to find self-organization opportunities (or necessities) bewildering -- there's kind of a tacit "who's in charge" question floated, a 'holding back' waiting for someone to direct the group.
Modern financial systems exhibit a high degree of interdependence. There are different possible sources of connections between financial institutions, stemming from both the asset and the liability side of their balance sheet. For instance, banks are directly connected through mutual exposures acquired on the interbank market. Likewise, holding similar portfolios or sharing the same mass of depositors creates indirect linkages between financial institutions. Broadly understood as a collection of nodes and links between nodes, networks can be a useful representation of financial systems.
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