Real-Time Detection of Traffic From Twitter Stream Analysis
By Eleonora D'Andrea, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni. IEEE transactions on intelligent transportation systems (Print), 2015
334 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/f192f4154639d0cda40a7fcaf5ebf31b9e411214
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In Computer Networks and Communications
In Information Systems
In Statistical and Nonlinear Physics
Citations in the corpus
- Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management (2020, background): “In this era, people extensively publish their daily activities and current locations on social network and social media, which have become an inseparable part of our everyday lives [10].”
- Computing Urban Traffic Congestions by Incorporating Sparse GPS Probe Data and Social Media Data (2017, background): “Most previous works focused on investigating either how to extract and visualize the traffic event information from tweets [Endarnoto et al. 2011; D’Andrea et al. 2015; Liu et al. 2014; Schulz et al. 2013] or how to locate the traffic events mentioned in the tweets [Daly et al.”
- Citywide traffic congestion estimation with social media (2015, background): “With the prevalence of social media, more and more works have tried to utilize Twitter as a new data source for detecting or monitoring traffic events [17, 5, 7, 19, 4, 3, 10].”