Abstract
Social media networks are dynamic. As such, the order in which network ties develop is an important aspect of the network dynamics.This study proposes a novel dynamic network model, the Nodal Attribute-based Temporal Exponential Random Graph Model (NATERGM) for dynamic network analysis. The proposed model focuses on how the nodal attributes of a network affect the order in which the network ties develop. Empirical results showed that the NATERGM demonstrated an enhanced pattern testing capability compared to benchmark models. The proposed NATERGM model helps explain the roles of nodal attributes in the formation process of dynamic networks.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1458-1459 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781509020195 |
| DOIs | |
| State | Published - Jun 22 2016 |
| Event | 32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland Duration: May 16 2016 → May 20 2016 |
Other
| Other | 32nd IEEE International Conference on Data Engineering, ICDE 2016 |
|---|---|
| Country | Finland |
| City | Helsinki |
| Period | 5/16/16 → 5/20/16 |
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Keywords
- dynamic networks
- knowledge sharing
- social media
ASJC Scopus subject areas
- Artificial Intelligence
- Computational Theory and Mathematics
- Computer Graphics and Computer-Aided Design
- Computer Networks and Communications
- Information Systems
- Information Systems and Management
Cite this
NATERGM : A model for examining the role of Nodal Attributes in dynamic social media networks. / Jiang, Shan; Chen, Hsinchun.
2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1458-1459 7498373.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - NATERGM
T2 - A model for examining the role of Nodal Attributes in dynamic social media networks
AU - Jiang, Shan
AU - Chen, Hsinchun
PY - 2016/6/22
Y1 - 2016/6/22
N2 - Social media networks are dynamic. As such, the order in which network ties develop is an important aspect of the network dynamics.This study proposes a novel dynamic network model, the Nodal Attribute-based Temporal Exponential Random Graph Model (NATERGM) for dynamic network analysis. The proposed model focuses on how the nodal attributes of a network affect the order in which the network ties develop. Empirical results showed that the NATERGM demonstrated an enhanced pattern testing capability compared to benchmark models. The proposed NATERGM model helps explain the roles of nodal attributes in the formation process of dynamic networks.
AB - Social media networks are dynamic. As such, the order in which network ties develop is an important aspect of the network dynamics.This study proposes a novel dynamic network model, the Nodal Attribute-based Temporal Exponential Random Graph Model (NATERGM) for dynamic network analysis. The proposed model focuses on how the nodal attributes of a network affect the order in which the network ties develop. Empirical results showed that the NATERGM demonstrated an enhanced pattern testing capability compared to benchmark models. The proposed NATERGM model helps explain the roles of nodal attributes in the formation process of dynamic networks.
KW - dynamic networks
KW - knowledge sharing
KW - social media
UR - http://www.scopus.com/inward/record.url?scp=84980371866&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84980371866&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2016.7498373
DO - 10.1109/ICDE.2016.7498373
M3 - Conference contribution
AN - SCOPUS:84980371866
SP - 1458
EP - 1459
BT - 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -