Abstract
In recent social network studies, exponential random graph (ERG) models have been used comprehensively to model global social network structure as a function of their local features. In this study, we describe the ERG models and demonstrate its use in modelling the changing communication network structure at Enron Corporation during the period of its disintegration. We illustrate the modelling on communication networks, and provide a new way of classifying networks and their performance based on the occurrence of their local features. Among several micro-level structures of ERG models, we find significant variation in the appearance of A2P (Alternating k-two-paths) network structure in the communication network during crisis period and non-crisis period. We also notice that the attribute of hierarchical positions of actors (i. e., high rank versus low rank staff) have impact on the evolution process of networks during crisis. These findings could be used in analyzing communication networks of dynamic project groups and their adaptation process during crisis which could lead to an improved understanding how communications network evolve and adapt during crisis.
| Original language | English |
|---|---|
| Pages (from-to) | 25-41 |
| Number of pages | 17 |
| Journal | Computational and Mathematical Organization Theory |
| Volume | 19 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Mar 2013 |
| Externally published | Yes |
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Exploring communication networks to understand organizational crisis using exponential random graph models. / Uddin, Shahadat; Hamra, Jafar; Hossain, Liaquat.
In: Computational and Mathematical Organization Theory, Vol. 19, No. 1, 03.2013, p. 25-41.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - Exploring communication networks to understand organizational crisis using exponential random graph models
AU - Uddin, Shahadat
AU - Hamra, Jafar
AU - Hossain, Liaquat
PY - 2013/3
Y1 - 2013/3
N2 - In recent social network studies, exponential random graph (ERG) models have been used comprehensively to model global social network structure as a function of their local features. In this study, we describe the ERG models and demonstrate its use in modelling the changing communication network structure at Enron Corporation during the period of its disintegration. We illustrate the modelling on communication networks, and provide a new way of classifying networks and their performance based on the occurrence of their local features. Among several micro-level structures of ERG models, we find significant variation in the appearance of A2P (Alternating k-two-paths) network structure in the communication network during crisis period and non-crisis period. We also notice that the attribute of hierarchical positions of actors (i. e., high rank versus low rank staff) have impact on the evolution process of networks during crisis. These findings could be used in analyzing communication networks of dynamic project groups and their adaptation process during crisis which could lead to an improved understanding how communications network evolve and adapt during crisis.
AB - In recent social network studies, exponential random graph (ERG) models have been used comprehensively to model global social network structure as a function of their local features. In this study, we describe the ERG models and demonstrate its use in modelling the changing communication network structure at Enron Corporation during the period of its disintegration. We illustrate the modelling on communication networks, and provide a new way of classifying networks and their performance based on the occurrence of their local features. Among several micro-level structures of ERG models, we find significant variation in the appearance of A2P (Alternating k-two-paths) network structure in the communication network during crisis period and non-crisis period. We also notice that the attribute of hierarchical positions of actors (i. e., high rank versus low rank staff) have impact on the evolution process of networks during crisis. These findings could be used in analyzing communication networks of dynamic project groups and their adaptation process during crisis which could lead to an improved understanding how communications network evolve and adapt during crisis.
KW - Email communications
KW - Exponential random graph models
KW - Organizational disintegration
KW - p models
KW - Social networks
KW - Statistical models for social networks
UR - http://www.scopus.com/inward/record.url?scp=84874412148&partnerID=8YFLogxK
U2 - 10.1007/s10588-011-9104-8
DO - 10.1007/s10588-011-9104-8
M3 - Article
VL - 19
SP - 25
EP - 41
JO - Computational and Mathematical Organization Theory
JF - Computational and Mathematical Organization Theory
SN - 1381-298X
IS - 1
ER -