Showing papers in "Social Networks in 2000"

TL;DR: This paper seeks to formalize the intuitive notion of a core/periphery structure and suggests algorithms for detecting this structure, along with statistical tests for testing a priori hypotheses.

TL;DR: A new formalization of a “node-centrality” is provided which leads to some properties a measure of centrality has to satisfy, which allow to test given measures, for example measures based on degree, closeness, betweenness or Bonacich’s eigenvector- centrality.

TL;DR: Using a national sample of individual's personal networks, the paper reveals that transitivity explains a majority of cases of network integration with two important caveats: recent work on networks and social structure points to important structural constraints on personal networks that shape their formation and homophily improves the likelihood of integration in personal networks.

TL;DR: Not forgetting is a pervasive, non-trivial phenomenon in the recall-based elicitation of personal and social networks pertaining to a broad variety of social relations and non-specific prompting for additional relevant persons, multiple elicitation questions, and re-interviewing enhance recall slightly to moderately and are the only methods currently available to counteract forgetting.

TL;DR: Recalled and forgotten friends do not differ appreciably in terms of their individual characteristics, although residents on average had modestly closer relationships with recalled friends than forgotten friends.

TL;DR: An experiment embedded within an interviewer-administered survey of 426 college students to explore the effects on reported network size and composition ofName-generator wording manipulations produced modest network compositional differences that varied by the sex of both egos and their alters.

TL;DR: Two relational power measures, the β - measure and the score-measure, are axiomatically characterized and applied to weighted directed networks that can be interpreted as dominance structures which dominance relations are assigned weights representing the ‘importance’ of each relation.

TL;DR: Some techniques for analysis of large networks (different approaches to identify ‘interesting’ individuals and groups, analysis of internal structure of the main core using pre-specified blockmodeling and hierarchical clustering) and visualizations of their parts are presented.

TL;DR: This paper discusses an approach based on Markov chain Monte Carlo techniques, and shows how to apply it to distributions in which all sociomatrices with other given totals are equally likely.

TL;DR: New measures of centrality that summarize the contact structure of social networks are proposed that consider all the possible paths, do not require intensive computer calculations, and can be used to compare networks of different sizes because they are independent of the size of the networks.

TL;DR: A dynamic process model of utility maximizing social actors embedded within social networks is developed, and two types of simulation models were developed: a multi-thread “real time” model, and a discrete event model.

TL;DR: This paper explores ways of identifying actors that are not members of a given cohesive subgroup, but who are sufficiently well tied to the group to be considered peripheral members, and uses this information to explore the structure of the network as a whole.

TL;DR: There is a strong relationship between the reported behavior of egos and their reports of their alters’ behavior, as others have done elsewhere, but levels of network stability and reciprocity were also low.

TL;DR: The social networks of visually impaired and blind adolescents are examined to examine if individual characteristics, including sociodemographic and vision-related characteristics, predict the aspects of the network, and if individual and network characteristics predict well-being.

TL;DR: Information on landcover from satellite digital data provides insights into the patterns of network ties throughout the district and shows a clear relationship between tractor hiring networks and type of agricultural activity in the district.

TL;DR: The results show that the personal networks of the Dutch are homogenous with respect to religion, education and social status, and members of personal networks have significant effects on the respondent’s voting behavior, effects that are stronger for social ties characterized by intimate contact.

TL;DR: Investigation of longitudinal data on individuals who recently experienced the death of an elderly family member for whom they were caring, and members of their social networks demonstrated that experiential similarity was important in explaining both men’s and women”s patterns of emotional support during bereavement.

TL;DR: It is argued that criticisms of correspondence analysis as a technique for analyzing two-mode network data are not justified and that correspondence analysis of such data can in fact yield considerable substantive insight.

TL;DR: Two algorithms based on Freeman's clique–lattice analysis are described, one implements his technique exactly; the second is a modification that exploits the clique structure, thereby enabling the analysis of large complex networks.

TL;DR: It is shown that exchange networks with dynamic structures can be analyzed using Network Exchange Theory (NET) even though that theory was developed with only static networks in mind.

TL;DR: This paper clarifies some major principles regarding the distribution of power in mixed exchange networks where both substitutability and complementarity exist among multiple exchange relations of an actor.

TL;DR: This paper presents the different measures for TTM, their interpretation and their advantages and disadvantages, and explores the distribution of the number of mutual dyads in graphs which are distributed according to a uniform distribution over certain special spaces.

TL;DR: A model of popularity structure in social networks is introduced where popularity is viewed as a latent attribute of the individuals in the network, composed of individuals from different popularity groups.