Behaviour Dynamics in Social Networks

2018-2019

Course Objective

To learn how to identify different types of mental
and social processes; to understand how individual and social behaviour
emerges from mechanisms known from Cognitive, Affective and Social
Neuroscience, and from Cognitive and Social Sciences; to be able to
construct network models for mental and social interaction processes; to
perform analysis based on these models using Network-Oriented Modeling
software tools and empirical data.

Course Content

This course is a multidisciplinary course, also accessible for students
from other disciplines such as Neuroscience, Psychology or Social
Sciences. Behaviour dynamics occurs in different forms, contexts and
complexity. Complexity can occur in the mental processes within persons
or in social interaction processes, or in both. Both types of processes
can be adaptive: mental processes can change due to learning, and social
interactions can also evolve over time. Theories and findings from
Cognitive, Affective and Social Neuroscience and also from Cognitive and
Social Sciences are presented and used to get insight in the underlying
mechanisms that form a solid scientific basis for modelling of these
processes. In the course a Network-Oriented Modeling approach based on
temporal-causal networks is used to model both these internal mental
processes (as networks of mental states) and social interaction
processes (as social networks). During the course several examples are
studied. These examples cover imagination and dreaming by internal
simulation, integration of emotions in all kinds of mental and social
processes, learning of emotion regulation, ownership and attribution of
actions, empathic social responses, empathic joint decision making,
development of shared understanding and collective action, and different
principles for evolving social networks.
The dynamics of such processes is modeled, simulated and analysed
(including verification and validation) in this course using dedicated
and easy to use modelling environments for Network-Oriented Modeling; no
programming is needed. In the last few weeks of the course a more
ambitious final assignment is addressed, which can be worked out to a
paper that may be submitted to an international conference where it
could be presented and provide a publication.

Teaching Methods

Combinations of lectures and practical assignments.

Method of Assessment

Practical assignments and a final assignment.
Presentation of the final assignment

Literature

Treur, J., Network-Oriented Modeling: Addressing Complexity of
Cognitive, Affective and Social Interactions. Series on Understanding
Complex Systems, Springer Publishers, October 2016.
URL: http://www.springer.com/gp/book/9783319452111#aboutBook
Free downloadable from the VU at doi:
http://dx.doi.org/10.1007/978-3-319-45213-5
Table of Contents: http://www.few.vu.nl/~treur/cve/Papers/NOMToC.pdf

Target Audience

mAI and multidisciplinary master studies from Psychology, Neuroscience
and
Social Sciences

Recommended background knowledge

None

General Information

Course Code X_400113
Credits 6 EC
Period P2
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator prof. dr. J. Treur
Examiner prof. dr. J. Treur
Teaching Staff prof. dr. J. Treur

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Practical
Target audiences

This course is also available as: