Gerador de dados sintéticos para dados de redes sociais baseados em localização

Abstract

Increasing restrictions imposed by data protection laws, combined with limited access to information from social media platforms, have posed significant challenges for research that relies on spatial, temporal, and behavioral data. In response to this scenario, this project proposes the development of a tool aimed at generating synthetic data that reproduces typical characteristics of digital social networks, without relying on personal information and in accordance with current ethical and legal standards. The proposed solution focuses on producing georeferenced points distributed in a configurable manner, based on areas of interest defined by layered spatial files and usage of demographic and economical information. The implementation is based on open-source technologies, allowing users to configure parameters such as point density, spatial granularity, and the exclusion of specific regions from the generation process. This structure supports a wide range of applications, including network algorithm testing, urban mobility analysis, and simulations of social behavior.