Human mobility modeling at metropolitan scales
By Sibren Isaacman, Richard A. Becker, Ramón Cáceres, Margaret Martonosi, James R. Rowland, Alex Varshavsky, Walter Willinger. 2012
329 citations recorded by the source corpus.
Subfields: Automotive Engineering, Computer Networks and Communications, Transportation
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
In Computer Networks and Communications
- Ramón Cáceres
- Tian He
- Rebecca N. Wright
- Margaret Martonosi
- Raja Jurdak
- Mark A. Cameron
- David Newth
- J. Stankovic
In Transportation
- Ramón Cáceres
- Margaret Martonosi
- Sibren Isaacman
- Tian He
- Raja Jurdak
- Kun Zhao
- Mark A. Cameron
- Maurice AbouJaoude
Citations in the corpus
- Understanding Human Mobility from Twitter (2014, background): “The insight from this article on mobility dynamics from tweets also lays the groundwork to generate synthetic mobility data [41] at various spatial scales for analysis of disease spread, transport systems or communication networks.”
- DP-WHERE: Differentially private modeling of human mobility (2013, methodology): “We further used this information to characterize commute distances, to quantify carbon footprints, and to create WHERE models [16, 19].”
- Exploring human mobility with multi-source data at extremely large metropolitan scales (2014, background): “But based on our empirical results in Section 3, an approach based on data from one type of transit has a bias against residents using other types of transit.”