The effect of recency to human mobility

• Published in: EPJ data science 2015-12, Vol.4 (1), p.21, Article 21
• Main Authors: Barbosa, Hugo, de Lima-Neto, Fernando B, Evsukoff, Alexandre, Menezes, Ronaldo
• Format: Article
• Language: English
• Subjects: Complexity; Computer Appl. in Social and Behavioral Sciences; Computer Science; Data-driven Science; Disaster relief; Disease spread; Exploitation; Human motion; Mobility; Modeling and Theory Building; Regular Article; Scientists; Urban planning; Wireless networks
• ISSN: 2193-1127; 2193-1127
• DOI: 10.1140/epjds/s13688-015-0059-8

In recent years, we have seen scientists attempt to model and explain human dynamics and in particular human movement. Many aspects of our complex life are affected by human movement such as disease spread and epidemics modeling, city planning, wireless network development, and disaster relief, to name a few. Given the myriad of applications, it is clear that a complete understanding of how people move in space can lead to considerable benefits to our society. In most of the recent works, scientists have focused on the idea that people movements are biased towards frequently-visited locations. According to them, human movement is based on a exploration/exploitation dichotomy in which individuals choose new locations (exploration) or return to frequently-visited locations (exploitation). In this work we focus on the concept of recency . We propose a model in which exploitation in human movement also considers recently-visited locations and not solely frequently-visited locations. We test our hypothesis against different empirical data of human mobility and show that our proposed model replicates the characteristic patterns of the recency bias.