The Effect of Recency to Human Mobility
April 07, 2015 Β· Declared Dead Β· π EPJ Data Science
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Hugo Barbosa, Fernando Buarque de Lima Neto, Alexandre Evsukoff, Ronaldo Menezes
arXiv ID
1504.01442
Category
physics.soc-ph
Cross-listed
cs.SI
Citations
76
Venue
EPJ Data Science
Last Checked
5 months ago
Abstract
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.soc-ph
π
π
The Cartographer
R.I.P.
π»
Ghosted
Networks beyond pairwise interactions: structure and dynamics
R.I.P.
π»
Ghosted
Statistical physics of human cooperation
R.I.P.
π»
Ghosted
Vital nodes identification in complex networks
R.I.P.
π»
Ghosted
Influence maximization in complex networks through optimal percolation
R.I.P.
π»
Ghosted
Scale-free networks are rare
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted