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A Randomized Approach for Structural and Message Based Private Friend Recommendation in Online Social Networks Read chapter Read first chapter

2014 | OriginalPaper | Chapter

An Agent-Based Modeling Framework for Social Network Simulation

Author : Enrico Franchi

Published in: State of the Art Applications of Social Network Analysis

Publisher: Springer International Publishing

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Abstract

Agent-based modeling has been frequently adopted as a research tool in the fields of social and political sciences. Although recently social network analysis has generated a new wave of interest in many different research fields, nonetheless software instruments specifically created for agent-based social network simulation are still missing. However, restricting the field of interest specifically to social network models and simulations instead of supporting general agent-based ones, allows for the creation of easier to use, more focused tools. In this work, we propose an agent-based modeling framework for simulations over social networks. The models are written in a purposely developed, domain-specific language that helps in mapping social-network concepts to agent-based ones. Our framework is created to deal with large simulations and to work effortlessly with other social network analysis toolkits.

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previous chapter Fast Exact and Approximate Computation of Betweenness Centrality in Social Networks
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Metadata
Title
An Agent-Based Modeling Framework for Social Network Simulation
Author
Enrico Franchi
Copyright Year
2014
Book
State of the Art Applications of Social Network Analysis

Print ISBN: 978-3-319-05911-2

Electronic ISBN: 978-3-319-05912-9

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-05912-9_4

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