NATERGM: A model for examining the role of Nodal Attributes in dynamic social media networks

Shan Jiang; Hsinchun Chen

doi:10.1109/ICDE.2016.7498373

NATERGM: A model for examining the role of Nodal Attributes in dynamic social media networks

Shan Jiang, Hsinchun Chen

Management Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

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	https://doi.org/10.1109/ICDE.2016.7498373
State	Published - Jun 22 2016
Event	32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland Duration: May 16 2016 → May 20 2016

Publication series

Name	2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

Other

Other	32nd IEEE International Conference on Data Engineering, ICDE 2016
Country/Territory	Finland
City	Helsinki
Period	5/16/16 → 5/20/16

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

Access to Document

10.1109/ICDE.2016.7498373

Cite this

Jiang, S., & Chen, H. (2016). NATERGM: A model for examining the role of Nodal Attributes in dynamic social media networks. In 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016 (pp. 1458-1459). [7498373] (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDE.2016.7498373

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 (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jiang, S & Chen, H 2016, NATERGM: A model for examining the role of Nodal Attributes in dynamic social media networks. in 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016., 7498373, 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1458-1459, 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, 5/16/16. https://doi.org/10.1109/ICDE.2016.7498373

Jiang S, Chen H. NATERGM: A model for examining the role of Nodal Attributes in dynamic social media networks. In 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1458-1459. 7498373. (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016). https://doi.org/10.1109/ICDE.2016.7498373

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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.",

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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.

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NATERGM: A model for examining the role of Nodal Attributes in dynamic social media networks

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Keywords

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