Abstract
This article presents a stochastic opinion dynamics model where (a) the opinion of each agent in a network is modeled as a probability distribution as against a point object, (b) consensus is defined as the stability region of the ensuing set of stochastic difference equations, and (c) compromise solutions can be derived between agents who don't have a consensus. The model is well suited for tracking opinion dynamics over large online systems such as Twitter and Yelp where opinions need to be extracted from the user-generated text data. Theoretical conditions for the existence of consensus and the impact that stubborn agents have on opinion dynamics are also presented.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 20-42 |
| Number of pages | 23 |
| Journal | International Journal of Business Analytics |
| Volume | 6 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2019 |
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Keywords
- Consensus
- Opinion Dynamics
- Opinion Formation
- Opinion Update
- Stochastic Difference Equations
ASJC Scopus subject areas
- Business and International Management
- Strategy and Management
Cite this
A mathematical foundation for stochastic opinion dynamics. / Castro, Luis E.; Shaikh, Nazrul I.
In: International Journal of Business Analytics, Vol. 6, No. 1, 01.01.2019, p. 20-42.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A mathematical foundation for stochastic opinion dynamics
AU - Castro, Luis E.
AU - Shaikh, Nazrul I
PY - 2019/1/1
Y1 - 2019/1/1
N2 - This article presents a stochastic opinion dynamics model where (a) the opinion of each agent in a network is modeled as a probability distribution as against a point object, (b) consensus is defined as the stability region of the ensuing set of stochastic difference equations, and (c) compromise solutions can be derived between agents who don't have a consensus. The model is well suited for tracking opinion dynamics over large online systems such as Twitter and Yelp where opinions need to be extracted from the user-generated text data. Theoretical conditions for the existence of consensus and the impact that stubborn agents have on opinion dynamics are also presented.
AB - This article presents a stochastic opinion dynamics model where (a) the opinion of each agent in a network is modeled as a probability distribution as against a point object, (b) consensus is defined as the stability region of the ensuing set of stochastic difference equations, and (c) compromise solutions can be derived between agents who don't have a consensus. The model is well suited for tracking opinion dynamics over large online systems such as Twitter and Yelp where opinions need to be extracted from the user-generated text data. Theoretical conditions for the existence of consensus and the impact that stubborn agents have on opinion dynamics are also presented.
KW - Consensus
KW - Opinion Dynamics
KW - Opinion Formation
KW - Opinion Update
KW - Stochastic Difference Equations
UR - http://www.scopus.com/inward/record.url?scp=85059760081&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059760081&partnerID=8YFLogxK
U2 - 10.4018/IJBAN.2019010102
DO - 10.4018/IJBAN.2019010102
M3 - Article
AN - SCOPUS:85059760081
VL - 6
SP - 20
EP - 42
JO - International Journal of Business Analytics
JF - International Journal of Business Analytics
SN - 2334-4547
IS - 1
ER -