The Effect of Recency to Human Mobility
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Abstract (arXiv)
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 movements 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 huge 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 an 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 is able to better explain the human trajectories in these datasets.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Apr 2015.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 2; 2026: 1.
6 papers.
- 2023Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulationcited by 15
- 2024Pretrained Mobility Transformer: A Foundation Model for Human Mobilitycited by 8
- 2022Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacycited by 6
- 2025Deep Generative Model for Human Mobility Behaviorcited by 0
- 2025M-STAR: Multi-Scale Spatiotemporal Autoregression for Human Mobility Modelingcited by 0
- 2026Detecting Transportation Mode Using Dense Smartphone GPS Trajectories and Transformer Modelscited by 0
- 2026Detecting Transportation Mode Using Dense Smartphone GPS Trajectories and Transformer Models27 Feb 2026
- 2025M-STAR: Multi-Scale Spatiotemporal Autoregression for Human Mobility Modeling8 Dec 2025
- 2025Deep Generative Model for Human Mobility Behavior7 Oct 2025
- 2024Pretrained Mobility Transformer: A Foundation Model for Human Mobility29 May 2024
- 2023Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulation15 Jun 2023
- 2022Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy4 Jan 2022