A Reexamination of Connectivity Trends via Exponential Random Graph Modeling in Two IDU Risk Networks

被引：16

作者：

Dombrowski, Kirk ^{[1
]}

Khan, Bilal ^{[2
]}

McLean, Katherine ^{[3
]}

Curtis, Ric ^{[2
]}

Wendel, Travis ^{[4
]}

Misshula, Evan ^{[3
]}

Friedman, Samuel ^{[5
]}

机构：

[1] Univ Nebraska, Dept Sociol, Lincoln, NE 68588 USA

[2] CUNY, John Jay Coll, New York, NY 10021 USA

[3] CUNY Grad Ctr, New York, NY USA

[4] CUNY, John Jay Coll, Social Networks Res Grp, New York, NY 10021 USA

[5] IAR, NDRI, New York, NY USA

来源：

SUBSTANCE USE & MISUSE | 2013年 / 48卷 / 14期

基金：

美国国家科学基金会;

关键词：

injector networks; ERGM; HIV transmission; network modeling; social network analysis; IDU; SFHR network; INJECTING DRUG-USERS; P-ASTERISK MODELS; INFECTIOUS-DISEASE; HIV; SEROPREVALENCE; BALTIMORE; EPIDEMIC; DYNAMICS; EXCHANGE; AIDS;

D O I：

10.3109/10826084.2013.796987

中图分类号：

R194 [卫生标准、卫生检查、医药管理];

学科分类号：

摘要：

Patterns of risk in injecting drug user (IDU) networks have been a key focus of network approaches to HIV transmission histories. New network modeling techniques allow for a reexamination of these patterns with greater statistical accuracy and the comparative weighting of model elements. This paper describes the results of a reexamination of network data from the SFHR and P90 data sets using Exponential Random Graph Modeling. The results show that "transitive closure" is an important feature of IDU network topologies, and provides relative importance measures for race/ethnicity, age, gender, and number of risk partners in predicting risk relationships.

引用

页码：1485 / 1497

页数：13

共 50 条

[1] Exponential random graph modeling of emergency collaboration networks
Hossain, Liaquat
Hamra, Jafar
Wigand, Rolf T.
Carlsson, Sven
[J]. KNOWLEDGE-BASED SYSTEMS, 2015, 77 : 68 - 79
[2] Exponential Random Graph Modeling for Complex Brain Networks
Simpson, Sean L.
Hayasaka, Satoru
Laurienti, Paul J.
[J]. PLOS ONE, 2011, 6 (05):
[3] Exponential Random Graph Modeling of Communication Networks to Understand Organizational Crisis
Hamra, Jafar
Uddin, Shahadat
Hossain, Liaquat
[J]. SIGMIS CPR 2011: PROCEEDINGS OF THE 2011 ACM SIGMIS COMPUTER PERSONNEL RESEARCH CONFERENCE, 2011, : 71 - 78
[4] Estimation of Exponential Random Graph Models for Large Social Networks via Graph Limits
He, Ran
Zheng, Tian
[J]. 2013 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM), 2013, : 254 - 261
[5] Learning Common Knowledge Networks Via Exponential Random Graph Models
Liu, Xueying
Hu, Zhihao
Deng, Xinwei
Kuhlman, Chris J.
[J]. PROCEEDINGS OF THE 2023 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING, ASONAM 2023, 2023, : 213 - 220
[6] An exponential random graph modeling approach to creating group-based representative whole-brain connectivity networks
Simpson, Sean L.
Moussa, Malaak N.
Laurienti, Paul J.
[J]. NEUROIMAGE, 2012, 60 (02) : 1117 - 1126
[7] Modeling Unobserved Heterogeneity in Social Networks with the Frailty Exponential Random Graph Model
Box-Steffensmeier, Janet M.
Christenson, Dino P.
Morgan, Jason W.
[J]. POLITICAL ANALYSIS, 2018, 26 (01) : 3 - 19
[8] Modeling Valued Organizational Communication Networks Using Exponential Random Graph Models
Pilny, Andrew
Atouba, Yannick
[J]. MANAGEMENT COMMUNICATION QUARTERLY, 2018, 32 (02) : 250 - 264
[9] Differentially Private Generation of Social Networks via Exponential Random Graph Models
Liu, Fang
Eugenio, Evercita C.
Jin, Ick Hoon
Bowen, Claire McKay
[J]. 2020 IEEE 44TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2020), 2020, : 1695 - 1700
[10] Closure, connectivity and degree distributions: Exponential random graph (p*) models for directed social networks
Robins, Garry
Pattison, Pip
Wang, Peng
[J]. SOCIAL NETWORKS, 2009, 31 (02) : 105 - 117

← 1 2 3 4 5 →