Abstract
Opinion dynamics on networks has wide applications to empirical and engineered systems and profound prospects in the general study of complex systems. Many efforts have been devoted to understanding how opinion dynamics is affected by network topology. However, social interactions are best characterized as temporal networks in which ordering of interactions cannot be ignored. Temporal activity patterns including heterogeneous contact strength and interevent times, turnover edge/node dynamics, and daily patterns could have significant effects that would not be captured by static aggregate network representations. In this paper, we study the effects of such temporal patterns on the speed of consensus formation in various models of continuous opinion dynamics using four empirical data sets, including three human face-to-face networks from different real-world settings and a social insect interaction network. We find that static, aggregated networks consistently overestimate the speed of simulated consensus formation while weight heterogeneity associated with frequency of interactions has an inhibitory effect on consensus formation relative to the behavior on unweighted networks. Moreover, the speed of consensus formation is found to be highly sensitive to nodal lifetimes, suggesting that randomization protocols that dramatically alter the distribution of lifetimes cannot be relied upon as reference models. On the other hand, temporal patterns including burstiness of interevent times and the lifetime of edges are found to have insignificant effects on consensus formation. The sensitivity to nodal lifetimes is further demonstrated via synthetic networks generated by an activity-driven model with tunable nodal lifetimes.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1355-1370 |
| Number of pages | 16 |
| Journal | Physica A: Statistical Mechanics and its Applications |
| Volume | 523 |
| DOIs | |
| State | Published - Jun 1 2019 |
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Keywords
- Consensus formation
- Coordination
- Deffuant model
- Opinion dynamics
- Temporal networks
ASJC Scopus subject areas
- Statistics and Probability
- Condensed Matter Physics
Cite this
Impact of temporal network structures on the speed of consensus formation in opinion dynamics. / Li, Mingwu; Dankowicz, Harry.
In: Physica A: Statistical Mechanics and its Applications, Vol. 523, 01.06.2019, p. 1355-1370.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Impact of temporal network structures on the speed of consensus formation in opinion dynamics
AU - Li, Mingwu
AU - Dankowicz, Harry
PY - 2019/6/1
Y1 - 2019/6/1
N2 - Opinion dynamics on networks has wide applications to empirical and engineered systems and profound prospects in the general study of complex systems. Many efforts have been devoted to understanding how opinion dynamics is affected by network topology. However, social interactions are best characterized as temporal networks in which ordering of interactions cannot be ignored. Temporal activity patterns including heterogeneous contact strength and interevent times, turnover edge/node dynamics, and daily patterns could have significant effects that would not be captured by static aggregate network representations. In this paper, we study the effects of such temporal patterns on the speed of consensus formation in various models of continuous opinion dynamics using four empirical data sets, including three human face-to-face networks from different real-world settings and a social insect interaction network. We find that static, aggregated networks consistently overestimate the speed of simulated consensus formation while weight heterogeneity associated with frequency of interactions has an inhibitory effect on consensus formation relative to the behavior on unweighted networks. Moreover, the speed of consensus formation is found to be highly sensitive to nodal lifetimes, suggesting that randomization protocols that dramatically alter the distribution of lifetimes cannot be relied upon as reference models. On the other hand, temporal patterns including burstiness of interevent times and the lifetime of edges are found to have insignificant effects on consensus formation. The sensitivity to nodal lifetimes is further demonstrated via synthetic networks generated by an activity-driven model with tunable nodal lifetimes.
AB - Opinion dynamics on networks has wide applications to empirical and engineered systems and profound prospects in the general study of complex systems. Many efforts have been devoted to understanding how opinion dynamics is affected by network topology. However, social interactions are best characterized as temporal networks in which ordering of interactions cannot be ignored. Temporal activity patterns including heterogeneous contact strength and interevent times, turnover edge/node dynamics, and daily patterns could have significant effects that would not be captured by static aggregate network representations. In this paper, we study the effects of such temporal patterns on the speed of consensus formation in various models of continuous opinion dynamics using four empirical data sets, including three human face-to-face networks from different real-world settings and a social insect interaction network. We find that static, aggregated networks consistently overestimate the speed of simulated consensus formation while weight heterogeneity associated with frequency of interactions has an inhibitory effect on consensus formation relative to the behavior on unweighted networks. Moreover, the speed of consensus formation is found to be highly sensitive to nodal lifetimes, suggesting that randomization protocols that dramatically alter the distribution of lifetimes cannot be relied upon as reference models. On the other hand, temporal patterns including burstiness of interevent times and the lifetime of edges are found to have insignificant effects on consensus formation. The sensitivity to nodal lifetimes is further demonstrated via synthetic networks generated by an activity-driven model with tunable nodal lifetimes.
KW - Consensus formation
KW - Coordination
KW - Deffuant model
KW - Opinion dynamics
KW - Temporal networks
UR - http://www.scopus.com/inward/record.url?scp=85064744115&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064744115&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2019.04.206
DO - 10.1016/j.physa.2019.04.206
M3 - Article
AN - SCOPUS:85064744115
VL - 523
SP - 1355
EP - 1370
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
SN - 0378-4371
ER -