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geopro:pedro:networks [2008/04/30 12:13] pedrogeopro:pedro:networks [2009/03/30 17:10] (atual) pedro
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   * **Erdős number:** is a way of describing the "collaborative distance", in regard to mathematical papers, between an author and Paul Erdős, one of the most prolific writers of mathematical papers.   * **Erdős number:** is a way of describing the "collaborative distance", in regard to mathematical papers, between an author and Paul Erdős, one of the most prolific writers of mathematical papers.
   * **Dunbar's number:** the typical size of a social network is constrained to about 150 members due to possible limits in the capacity of the human communication channel.   * **Dunbar's number:** the typical size of a social network is constrained to about 150 members due to possible limits in the capacity of the human communication channel.
 +  * **social distance:** the shortest number of steps between 2 persons in a network.
 +  * **Fruchterman-Reingold algorithm**: Graph Drawing by Force-directed Placement (1991)
 +  * **Boolean network:** a set of Boolean variables whose state is determined by other variables in the network. They are a particular case of discrete dynamical networks, where time and states are discrete, i.e. they have a bijection onto an integer series. Boolean and elementary cellular automata are particular cases of Boolean networks.
  
 =====Motivation===== =====Motivation=====
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 {{  http://www.leg.ufpr.br/~pedro/figures/network-infoflow.jpg}} {{  http://www.leg.ufpr.br/~pedro/figures/network-infoflow.jpg}}
 +
  
 =====Papers===== =====Papers=====
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 Diffusion of innovations theory explores social networks and their role in influencing the spread of new ideas and practices. Change agents and opinion leaders often play major roles in spurring the adoption of innovations, although factors inherent to the innovations also play a role. Diffusion of innovations theory explores social networks and their role in influencing the spread of new ideas and practices. Change agents and opinion leaders often play major roles in spurring the adoption of innovations, although factors inherent to the innovations also play a role.
- 
-Dunbar's number: The rule of 150 suggested that the typical size of a social network is constrained to about 150 members due to possible limits in the capacity of the human communication channel. The rule arises from cross-cultural studies in sociology and especially anthropology of the maximum size of a village (in modern parlance most reasonably understood as an ecovillage). It is theorized in evolutionary psychology that the number may be some kind of limit of average human ability to recognize members and track emotional facts about all members of a group. However, it may be due to economics and the need to track "free riders", as it may be easier in larger groups to take advantage of the benefits of living in a community without contributing to those benefits. 
  
 Nevertheless, even as an average person may only be able to establish a few strong ties due to possible constraints of human communication channels, Mark Granovetter found in one study that more numerous weak ties can be important in seeking information and innovation. Cliques have a tendency to more homogeneous opinions as well as sharing many common traits. This homophillic tendency was the reason for the members of the cliques to be attracted together in the first place. However, being similar, each member of the clique would also know more or less what the other members knew. To find new information or insights, members of the clique will have to look beyond the clique to its other friends and acquaintances. This is what Granovetter called the "the strength of weak ties". Nevertheless, even as an average person may only be able to establish a few strong ties due to possible constraints of human communication channels, Mark Granovetter found in one study that more numerous weak ties can be important in seeking information and innovation. Cliques have a tendency to more homogeneous opinions as well as sharing many common traits. This homophillic tendency was the reason for the members of the cliques to be attracted together in the first place. However, being similar, each member of the clique would also know more or less what the other members knew. To find new information or insights, members of the clique will have to look beyond the clique to its other friends and acquaintances. This is what Granovetter called the "the strength of weak ties".
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-====Collective dynamics of `small-world' networks==== 
-|Watts, D J and Strogatz, S H, 1998| Nature  393(6684) 440-442| 
  
-\\ 
  
-**Abstract:** Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays,, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks `rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them `small-world' networks, by analogy with the small-world phenomenon, (popularly known as six degrees of separation). The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices. 
  
-\\ 
- 
- 
-====The Strength of Weak Ties==== 
-|M. S. Granovetter| Americal Journal of Sociology, 1973 78(6) 1360-1380| [[http://www.stanford.edu/dept/soc/people/mgranovetter/documents/granstrengthweakties.pdf|pdf]]| 
-{{  http://www.leg.ufpr.br/~pedro/figures/bridges.jpg}} 
-\\ 
- 
-**Abstract:** Analysis of social networks is suggested as a tool for linking micro and macro levels of sociological theory. The procedure is illustrated by elaboration of the macro implications of one aspect of small-scale interaction: **the strength of dyadic ties. It is argued that the degree of overlap of two individuals' friendship networks varies directly with the strength of their tie to one another. The impact of this principle on diffusion of influence and information, mobility opportunity, and community organization is explored.** Stress is laid on the cohesive power of weak ties. Most network models deal, implicitly, with strong ties, thus confining their applicability to small, well-defined groups. Emphasis on weak ties lends itself to discussion of relations //between// groups and to analysis of segments of social structure not easily defined in terms of primary groups. 
- 
-\\ 
- 
-**The strength of a tie is a (probabily linear) combination of the amount of time, the emotional intensity, the intimacy (multual confiding), and the reciprocal services which characterize the tie.** Ties are strong, weak, or absent. The stronger the tie between A and B, the larger the proportion of S to whom they will both be tied. The hypothesis is made plausible also by empirical evidence that the stronger the tie connecting two individuals, the more similar they are, in various ways. 
- 
-In the figure, A-B is a local bridge of degree 3 (above), and of degree 13 (below). As higher is the degree, stronger is the bridge. By the same logic used above, only weak ties may be local bridges. 
- 
-Tells about the problem of a participant observation to get information of a fairy restricted circle, and therefore do not take into account the weak ties. 
  
  
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 \\ \\
  
- +====Scale-free network of a dengue epidemic==== 
- +|E Massad, S Ma, M ChenStruchinerN StollenwerkM Aguiar2008Applied Mathematics and Computation 195:376381| [[http://www.leg.ufpr.br/~pedro/papers/amc/network-dengue.pdf|pdf]]|
- +
- +
- +
-====Geographic routing in social networks==== +
-{{ http://www.leg.ufpr.br/~pedro/figures/distance-and-friendship2.jpg}} +
-|D Liben-Nowel, J NovakR KumarP Raghavanand A Tomkins, 2005PNAS 102(33)  1162311628| [[http://www.leg.ufpr.br/~pedro/papers/pnas/geographic-routing-social-networks.pdf|pdf]]|+
  
 \\ \\
  
-**Abstract:**We live in a ‘‘small world,’’ where two arbitrary people are likely connected by a short chain of intermediate friends. With scant +**Abstract:** In this work we show that the dengue epidemic in the city of Singapore organized itself into scale-free network of 
-information about a target individual, people can successively forward a message along such a chainExperimental studies have +transmission as the 2000–2005 outbreaks progressedThis scale-free network of cluster comprised geographical breeding 
-verified this property in real social networksand theoretical models have been advanced to explain it. However, existing +places for the aedes mosquitoesacting as super-spreaders nodes in a network of transmissionThe geographical organization 
-theoretical models have not been shown to capture behavior in real-world social networksHere, we introduce a richer model +of the network was analysed by the corresponding distribution of weekly number of new casesThereforeour 
-relating geography and social-network friendship, in which the probability of befriending a particular person is inversely proportional +hypothesis is that the distribution of dengue cases reflects the geographical organization of a transmission networkwhich 
-to the number of closer peopleIn a large social networkwe show that one-third of the friendships are independent of geography +evolved towards a power law as the epidemic intensity progressed until 2005.
-and the remainder exhibit the proposed relationship. Furtherwe prove analytically that short chains can be discovered in +
-every network exhibiting the relationship.+
  
 \\ \\
- 
-at first blush, geographic location might have very little to do with the identity of a 
-person’s online friends, but Fig. 3A verifies that geography remains crucial in online friendship. 
-Although it has been suggested that the impact of distance is marginalized by communications technology 
-(26), a large body of research shows that proximity remains a critical factor in effective collaboration and that the negative impacts of 
-distance on productivity are only partially mitigated by technology (27). However, for distances larger than 1000 km, the  
-curve approximately flattens to a constant probability of friendship between people, regardless of the geographic distance between them. 
  
  
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 \\ \\
 +
  
 ====A network economic model for supply chain versus supply chain competition==== ====A network economic model for supply chain versus supply chain competition====
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 +
 +
 +
 +====Economic Action and Social Structure: The Problem of Embeddedness====
 +|M. Granovetter, 1985| American Journal of Sociology 91:481-510| [[http://www.leg.ufpr.br/~pedro/papers/embeddedness-social-structure-granovetter.pdf|pdf]]|
 +
 +\\
 +
 +**Abstract:** How behaviour and institutions are affected by social relations is one of the classic
 +questions of social theory. This paper concerns the extent to which economic action is embedded in
 +structures of social relations, in modern industrial society. Although the usual neoclassical 
 +accounts provide an "undersocialized" or atomized-actor explanation of such action, reformist 
 +economics who attempt to bring social structure back in do so in the "oversocialized" way 
 +criticized by Dennis Wrong. Under- and over socialized accounts are paradoxically similar in their
 +neglect of ongoing structures of social relations, and a sophisticated account of economic action 
 +must consider its embeddedness in such structures. The argument is illustrated by a critic of
 +Oliver Willamson's "markets and hierarchies" research program.
 +
 +\\
 +
 +
 +FIXME Checar a veracidade: the behaviour of individuals cannot be explained except in terms of their 
 +interaction with other individuals known to them. Individuals being influenced by other individuals
 +without slavishly imitating them.
 +
 +====Capturing Social Embeddedness: a constructivist approach====
 +|B Edmonds, 1999| Adaptive Behaviour 7:323-348| [[http://www.leg.ufpr.br/~pedro/papers/social-embeddedness-constructivist.pdf|pdf]]|
 +
 +\\
 +
 +**Abstract:** A constructivist approach is applied to characterising social embeddedness. Social embeddedness is
 +intended as a strong type of **social situatedness**. It is defined as the extent to which modelling the
 +behaviour of an agent requires the inclusion of other agents as individuals rather than as an
 +undifferentiated whole. Possible consequences of the presence of social embedding and ways to check
 +for it are discussed. A model of co-developing agents is exhibited which demonstrates the possibility of
 +social embedding. This is an extension of Brian Arthur’s ‘El Farol Bar’ model, with added learning and
 +communication. Some indicators of social embedding are analysed and some possible causes of social
 +embedding are discussed. It is suggested that social embeddedness may be an explanation of the causal
 +link between the social situatedness of the agent and it employing a constructivist strategy in its
 +modelling.
 +
 +\\
  
geopro/pedro/networks.1209557596.txt.gz · Última modificação: 2008/04/30 12:13 por pedro