@mastersthesis{TFG-gsi-mastersthesis-2018,
author = "M{\'e}ndez, Tasio",
abstract = "Agent-based Social Simulation tools have been developed as one of the applications of agent technology. It constitutes the intersection of three scientific fields, namely, agent-based computing, the social sciences, and computer simulation. Due to its increasingly use in social context, in this thesis, a web interface for its visualization is presented.

The aim of this project is to develop a web application which allows the user to visualize and analyze the results of a simulation. It allows the user to analyze data in real time and launch new simulations which can be configured from the web.
For this purpose, a model which tries to simulate the growth of radicalism in a society is developed. The model aims at improving the understanding of the influence of social links on radicalism spread. The model consists of two main entities, a spread model and a network model. The network model updates the agent relationships based on proximity and homophily, it simulates information diffusion and updates the agents’ beliefs.

The model has been implemented in Python with the agent-based social simulator Soil and it has been evaluated using a sensitivity analysis while the application uses D3.js, which is a powerful JavaScript library, for rendering the results of the simulation and analyze them.

This thesis is divided in three phases: the design and implementation of the visualization module, the analysis and research necessary to acquire the knowledge for modeling radicalism diffusion and the implementation of the model as well as making the application auto-configurable to simulate the model from it.",
address = "ETSI Telecomunicaci{\'o}n, Madrid",
institution = "ETSIT, Universidad Polit{\'e}cnica de Madrid",
keywords = "soil;Radicalization;web development;graphs;terrorism;social networks",
month = "June",
title = "{D}esign and {I}mplementation of a {V}isualization {M}odule for {A}gent-based {S}ocial {S}imulations applied to {R}adicalism {S}pread",
type = "TFG",
year = "2018",
}