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20162022
most citedOn the Use of ArXiv as a Dataset

23 citations · 30 across the 7 of their papers we have counts for

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6 papers · 1 filter

physics.soc-ph20201 cited

The darkweb: a social network anomaly

Kevin P. O'Keeffe, Virgil Griffith, Yang Xu +2

We analyse the darkweb and find its structure is unusual. For example, of darkweb sites \emph{never} link to another site. To call the darkweb a "web" is thus a misno…

physics.soc-ph20203 cited

The spectral dimension of human mobility

Lei Dong, Kevin O'Keeffe, Paolo Santi +5

Human mobility patterns are surprisingly structured. In spite of many hard to model factors, such as climate, culture, and socioeconomic opportunities, aggregate migration rates ob…

physics.soc-ph20192 cited

Using reinforcement learning to minimize taxi idle times

Kevin O'Keeffe, Sam Anklesaria, Paolo Santo +1

Taxis spend a significant amount of time idle, searching for passengers. The routes vacant taxis should follow in order to minimize their idle times are hard to calculate; they dep…

physics.soc-ph2019

Modeling vehicular mobility patterns using recurrent neural networks

Kevin O'Keeffe, Paolo Santi, Carlo Ratti

Data on vehicular mobility patterns have proved useful in many contexts. Yet generative models which accurately reproduce these mobility patterns are scarce. Here, we explore if re…

physics.soc-ph2019

Urban sensing as a random search process

Kevin O'Keeffe, Paolo Santi, Brandon Wang +1

We study a new random search process: the \textit{taxi-drive}. The motivation for this process comes from urban sensing, in which sensors are mounted on moving vehicles such as tax…

physics.soc-ph2018

Quantifying the sensing power of crowd-sourced vehicle fleets

Kevin P. O'Keeffe, Amin Anjomshoaa, Steven H. Strogatz +2

Sensors can measure air quality, traffic congestion, and other aspects of urban environments. The fine-grained diagnostic information they provide could help urban managers to moni…