Showing papers in "Social Networks in 2004"

TL;DR: In contrast to earlier analyses of scientific collaboration networks, mixing by degree between vertices is found to be disassortative and both the evolutionary trajectories of the average geodesic length and of the clustering coefficients are found to have minima.

TL;DR: Results suggest that measures of egocentric network properties based on data collected using a single name generator may have high levels of measurement error, possibly resulting in misestimation of how these network properties relate to other variables.

TL;DR: The insight that rows and columns can be partitioned in different ways can be applied also to one-mode data, illustrated by a partition of a journal-to-journal citation network where journals are viewed simultaneously as both producers and consumers of scientific knowledge.

TL;DR: The existence of ethnic boundaries in 20 pupils’ networks is tested by comparing the proportion of intra-ethnic to inter-ethnic relationships, while controlling for the distribution of inter- and intra- ethnic dyads in pupils' networks, and the p2 model was used.

TL;DR: A heuristic method based on pseudo-likelihood estimation is presented to infer whether certain structural effects may contribute substantially to the predictive capacity of a model, thereby enabling comparisons of important effects between models with differently sized node sets.

TL;DR: I am baking a cake and have run out of sugar, but I can go to my neighbor next door to get some, and in giving me a copy of the recipe my neighbor still has it, there is really nothing to return except for good will.

TL;DR: This paper suggests that similarity is due to both peer influence and selection among adolescents, and that peer networks contribute to similarity by providing a pattern of peer ties in which peer influence can flourish.

TL;DR: A new measure of status or network centrality that takes into account both positive and negative relationships is suggested, based on the eigenvector measure of centrality, a standard measure in network research.

TL;DR: The data shows no evidence for expectations about equalizing effects on the general structure of academic communication, and IDGs do not reduce inequalities in the opportunities to use informal communication channels.

TL;DR: In this paper, a survey of personal networks in the Toulouse area (France) allows us to demonstrate the importance of social circles in the genesis of dyadic relations, and to understand social structures, one must begin with relations.

TL;DR: This case permits a critical test of the protective versus harmful effects of social ties: a business that operated as a legitimate enterprise and also engaged in ongoing financial fraud.

TL;DR: This paper shows how the concept of network centrality can be adapted to supra-dyadic networks with data on attacks by inhabitants of Caribbean islands on Spanish settlements in the period 1509–1700.

TL;DR: This paper reformulate and clarify the definitions of basic biases, and derives from first principles the triad distribution in a biased net, using two different analytical strategies to check the derivations.

TL;DR: The structure of the social network of junior high school students from a low socioeconomic status and the association between centrality measurements and academic performance were described and the female gender and only study were significant predictors of high academic performance.

TL;DR: It is shown that random connections that make possible cooperator jump into defectors’ clusters ironically trigger the formation of defector’ niches, in which defectors impose upon cooperators and do not have incentive to change their strategy.

TL;DR: It is suggested that more positive regard tends to be accompanied by positive interaction that encourages more social interaction, such that positive regard by a dense set of alters especially encourages interaction with that set, and positive regard is associated with denser networks.

TL;DR: Duncan Watts and Albert-Ĺ aszĺ o Baŕabasi are the both physicists who have recently crashed the world of social networks, arousing some resentment in the process; profound and important differences between the two models they initiated are laid out.

TL;DR: This paper aggregates actor indices of centrality across actors to obtain a single group-level index of centralization, and assumes a general blockmodel which allows a rich probabilistic structure of graph centralization.

TL;DR: A dynamic analysis of participation in multilateral negotiations gives insight into the continuity and change of participation during a negotiating process, and quantitative methods seem to be useful for analyzing such a complex case.

TL;DR: The authors sincerely apologize to Martin and Steve Borgatti for not incorporating the work in their 1992 paper on generalized blockmodeling to two-mode data.

TL;DR: The author regrets that in the above published paper the following error occurred and referred to one centrality measure as “simple eigenvector” and another measure as“Bonacich 1972 eigen vector.”