The Network Autocorrelation Model using Two-mode Data: Affiliation Exposure and Potential Bias in the Autocorrelation Parameter [0.03%]
基于双模数据的网络自相关模型：隶属曝光与自相关参数潜在偏差之偏见分析
Kayo Fujimoto,Chih-Ping Chou,Thomas W Valente
Kayo Fujimoto
James Moody,Wendy D Brynildsen,D Wayne Osgood et al.
James Moody et al.
This paper introduces new longitudinal network data from the "Promoting School-Community-University Partnerships to Enhance Resilience" or "PROSPER" peers project. In 28 communities, grade-level sociometric friendship nominations were colle...
Matthew J Salganik,Maeve B Mello,Alexandre H Abdo et al.
Matthew J Salganik et al.
Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimate...
Thomas W Valente,Kayo Fujimoto
Thomas W Valente
This paper proposes several measures for bridging in networks derived from Granovetter's (1973) insight that links which reduce distances in a network are important structural bridges. Bridging is calculated by systematically deleting links...
SOCIAL NETWORK ANALYSIS WITH RESPONDENT-DRIVEN SAMPLING DATA: A STUDY OF RACIAL INTEGRATION ON CAMPUS [0.03%]
基于被访者驱动抽样数据的社交网络分析：一项关于校园种族融合的研究
Cyprian Wejnert
Cyprian Wejnert
This paper presents Respondent-Driven Sampling (RDS) as a viable method of sampling and analyzing social networks with survey data. RDS is a network based sampling and analysis method that provides a middle ground compliment to ego-centric ...
Identifying positions from affiliation networks: Preserving the duality of people and events [0.03%]
从隶属网络识别职位：保持人和事件的二元性
Sam Field,Kenneth A Frank,Kathryn Schiller et al.
Sam Field et al.
Frank's [Frank, K.A., 1995. Identifying cohesive subgroups. Social Networks 17, 27-56] clustering technique for one-mode social network data is adapted to identify positions in affiliation networks by drawing on recent extensions of p(*) mo...
Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models [0.03%]
具有潜在聚类随机效应的社交网络中的度分布、聚类和同质性表示模型研究
Pavel N Krivitsky,Mark S Handcock,Adrian E Raftery et al.
Pavel N Krivitsky et al.
Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesia...
David R Schaefer,John M Light,Richard A Fabes et al.
David R Schaefer et al.
The goal of this research was to investigate the origins of social networks by examining the formation of children's peer relationships in 11 preschool classes throughout the school year. We investigated whether several fundamental processe...
Benjamin Cornwell
Benjamin Cornwell
Bridges that span structural holes are often explained in terms of the entrepreneurial personalities or rational motivations of brokers, or structural processes that lead to the intersection of social foci. I argue that the existence and us...
Personality Disorder in Social Networks: Network Position as a Marker of Interpersonal Dysfunction [0.03%]
社交网络中的性格障碍：网络位置作为人际关系功能障碍的标志
Allan Clifton,Eric Turkheimer,Thomas F Oltmanns
Allan Clifton
The present study investigated social network position as a marker of interpersonal functioning in personality disorders. Participants were groups of military recruits (N=809) in 21 training groups. Participants completed self- and informan...