Abstract
In this paper a cognitive model is presented for sharing behaviour (retweeting) on Twitter, addressing the underlying cognitive and affective processes. The model explains how the use of emotions in addition to information can cause an amplification in the diffusion of this information. It was designed according to a Network-Oriented Modeling approach based on temporal-causal network models. By mathematical analysis of stationary points it was verified that the implemented network model does what is expected from the design of the model. In addition, the equilibrium equations of the network model were solved algebraically by a symbolic solver and the solutions were shown to relate well to empirically expected outcomes. Validation by parameter tuning was also performed, and also shows a good approximation of empirically expected outcomes.
| Language | English |
|---|---|
| Pages | 136-144 |
| Number of pages | 9 |
| Journal | Biologically Inspired Cognitive Architectures |
| Volume | 26 |
| DOIs | |
| State | Published - Oct 2018 |
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Bibliographical note
Available online 8 November 2018Cite this
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A temporal-causal network model for the effect of emotional charge on information sharing. / Schoenmaker, Rosa; Treur, Jan; Vetter, Boaz.
In: Biologically Inspired Cognitive Architectures, Vol. 26, 10.2018, p. 136-144.Research output: Contribution to Journal › Article › Academic › peer-review
TY - JOUR
T1 - A temporal-causal network model for the effect of emotional charge on information sharing
AU - Schoenmaker,Rosa
AU - Treur,Jan
AU - Vetter,Boaz
N1 - Available online 8 November 2018
PY - 2018/10
Y1 - 2018/10
N2 - In this paper a cognitive model is presented for sharing behaviour (retweeting) on Twitter, addressing the underlying cognitive and affective processes. The model explains how the use of emotions in addition to information can cause an amplification in the diffusion of this information. It was designed according to a Network-Oriented Modeling approach based on temporal-causal network models. By mathematical analysis of stationary points it was verified that the implemented network model does what is expected from the design of the model. In addition, the equilibrium equations of the network model were solved algebraically by a symbolic solver and the solutions were shown to relate well to empirically expected outcomes. Validation by parameter tuning was also performed, and also shows a good approximation of empirically expected outcomes.
AB - In this paper a cognitive model is presented for sharing behaviour (retweeting) on Twitter, addressing the underlying cognitive and affective processes. The model explains how the use of emotions in addition to information can cause an amplification in the diffusion of this information. It was designed according to a Network-Oriented Modeling approach based on temporal-causal network models. By mathematical analysis of stationary points it was verified that the implemented network model does what is expected from the design of the model. In addition, the equilibrium equations of the network model were solved algebraically by a symbolic solver and the solutions were shown to relate well to empirically expected outcomes. Validation by parameter tuning was also performed, and also shows a good approximation of empirically expected outcomes.
UR - http://www.scopus.com/inward/record.url?scp=85056082341&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056082341&partnerID=8YFLogxK
U2 - 10.1016/j.bica.2018.10.003
DO - 10.1016/j.bica.2018.10.003
M3 - Article
VL - 26
SP - 136
EP - 144
JO - Biologically Inspired Cognitive Architectures
T2 - Biologically Inspired Cognitive Architectures
JF - Biologically Inspired Cognitive Architectures
SN - 2212-683X
ER -