Estimating Mobile Traffic Demand Using Twitter

In this letter, the authors show that structured social media data can act as an accurate predictor for wireless data demand patterns at a high spatial-temporal resolution. A casestudy is performed on Greater London covering a 5000 km 2 area. The data used includes over 0.6 million geo-tagged Twitte...

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Veröffentlicht in:	IEEE wireless communications letters 2016-08, Vol.5 (4), p.380-383
Hauptverfasser:	Yang, Bowei, Guo, Weisi, Chen, Bozhong, Yang, Guangpu, Zhang, Jie
Format:	Artikel
Sprache:	eng
Schlagworte:	Cellular networks Census Channels communication system traffic Correlation Data models Demand Digital media Mathematical models Media Mobile communication Social networks Sociology Traffic accidents & safety Traffic congestion Traffic engineering Traffic flow Twitter
Online-Zugang:	Volltext
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