Diffusion of Innovations: combining theoretical-computational models with real data observations

• Grant number: 16/20874-3
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: February 01, 2017
• End date: January 31, 2018
• Field of knowledge: Physical Sciences and Mathematics - Physics - General Physics
• Principal Investigator: José Fernando Fontanari
• Grantee: Sandro Martinelli Reia
• Supervisor: Santo Fortunato
• Host Institution: Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: Indiana University, United States
• Associated to the scholarship: 15/17277-0 - Diffusion of Innovations: a computational approach based on Axelrod's model, BP.PD

Abstract

Interest in learning how an innovation spreads in society has led researchers to develop theoretical-computational models to investigate the mechanisms that rule the diffusion of a new idea. In the current literature one may find epidemiological, cultural, and game models describing the community reaction to a novelty, where each type of modeling adopts a different approach to resemble some aspects of the collective behaviour. In addition, data mining techniques enable scientists to determine not only the topology of social networks that links different people but also the way they interact, so as to monitor the information flow as a function of the net structure. In this project, we aim to study the diffusion of innovations in a community of interacting agents by looking at real-world data from social systems.Subsequently, these data will be compared to the results obtained from different models in order to determine the best theoretical approach to describe the system under study.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

REIA, SANDRO M.. Diffusion of innovations in Axelrod's model on small-world networks. INTERNATIONAL JOURNAL OF MODERN PHYSICS C, v. 31, n. 8, AUG 2020. (16/20874-3, 15/17277-0)