Sender- and receiver-specific blockmodels
(2015) In Journal of Social Structure 16. p.1-34- Abstract
- We propose a sender-specific blockmodel for network data which utilizes both the group membership and the identities of the vertices.
This is accomplished by introducing the edge probabilities $(\theta_{i, v})$ for $1\le i\le c, 1\le v\le n$, where $i$ specifies the group membership of a sending vertex and $v$ specifies the identity of the receiving vertex. In addition, group membership is consider to be random, with parameters $(p_i)_{i=1}^c$. We present methods based on the EM algorithm for the parameter estimations and discuss the recovery of latent group memberships. A companion model, the receiver-specific blockmodel, is also introduced in which the edge probabilities $(\psi_{u, j})$ for $1\le u \le n,1\le j\le c$ depend on... (More) - We propose a sender-specific blockmodel for network data which utilizes both the group membership and the identities of the vertices.
This is accomplished by introducing the edge probabilities $(\theta_{i, v})$ for $1\le i\le c, 1\le v\le n$, where $i$ specifies the group membership of a sending vertex and $v$ specifies the identity of the receiving vertex. In addition, group membership is consider to be random, with parameters $(p_i)_{i=1}^c$. We present methods based on the EM algorithm for the parameter estimations and discuss the recovery of latent group memberships. A companion model, the receiver-specific blockmodel, is also introduced in which the edge probabilities $(\psi_{u, j})$ for $1\le u \le n,1\le j\le c$ depend on the membership of a vertex receiving a directed edge. We apply both models to several sets of social network data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8165926
- author
- Geng, Zhi LU and Nowicki, Krzysztof LU
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Directed graph, Blockmodeling, Out-nets, In-nets, Ego-nets, EM algorithm, Multinomial distribution
- in
- Journal of Social Structure
- volume
- 16
- pages
- 1 - 34
- publisher
- International Network for Social Network Analysis (INSNA)
- external identifiers
-
- scopus:84947760064
- ISSN
- 1529-1227
- language
- English
- LU publication?
- yes
- id
- 4c4dc634-80ff-446f-aa16-51684030dbef (old id 8165926)
- alternative location
- https://www.cmu.edu/joss/content/articles/volume16/GengNowicki.pdf
- date added to LUP
- 2016-04-01 14:48:02
- date last changed
- 2022-01-28 02:31:28
@article{4c4dc634-80ff-446f-aa16-51684030dbef,
abstract = {{We propose a sender-specific blockmodel for network data which utilizes both the group membership and the identities of the vertices.<br/><br>
This is accomplished by introducing the edge probabilities $(\theta_{i, v})$ for $1\le i\le c, 1\le v\le n$, where $i$ specifies the group membership of a sending vertex and $v$ specifies the identity of the receiving vertex. In addition, group membership is consider to be random, with parameters $(p_i)_{i=1}^c$. We present methods based on the EM algorithm for the parameter estimations and discuss the recovery of latent group memberships. A companion model, the receiver-specific blockmodel, is also introduced in which the edge probabilities $(\psi_{u, j})$ for $1\le u \le n,1\le j\le c$ depend on the membership of a vertex receiving a directed edge. We apply both models to several sets of social network data.}},
author = {{Geng, Zhi and Nowicki, Krzysztof}},
issn = {{1529-1227}},
keywords = {{Directed graph; Blockmodeling; Out-nets; In-nets; Ego-nets; EM algorithm; Multinomial distribution}},
language = {{eng}},
pages = {{1--34}},
publisher = {{International Network for Social Network Analysis (INSNA)}},
series = {{Journal of Social Structure}},
title = {{Sender- and receiver-specific blockmodels}},
url = {{https://www.cmu.edu/joss/content/articles/volume16/GengNowicki.pdf}},
volume = {{16}},
year = {{2015}},
}