TY - GEN
T1 - Passenger-centric metrics for air transportation leveraging mobile phone and twitter data
AU - Marzuoli, Aude
AU - Monmousseau, Philippe
AU - Feron, Eric
N1 - Generated from Scopus record by KAUST IRTS on 2021-02-18
PY - 2019/2/7
Y1 - 2019/2/7
N2 - This paper aims at presenting a detailed analysis of domestic air passengers behavior during a major air-traffic disturbance, from two complementary passenger-centric perspective: A passenger mobility perspective and a passenger social media perspective. By leveraging over 5 billion records of mobile phone location data per day from a major carrier in the United States, passenger mobility can be reliably analyzed, no matter which airline the passengers fly on or which airport they fly to and from. Such information is currently unavailable to the major aviation stakeholders at such scale and can be used to establish performance benchmarks from a passenger's perspective. Combining it with a Twitter analysis provides a more detailed and passenger-focused analysis than the traditional flight-centric measurements used to evaluate the overall system performance. More generally, these two passenger-centric analysis could be implemented in real-time for a daily evaluation of the Air Transportation System, enabling a faster analysis of the impact of major disruptions, whether due to meteorological conditions or system failures.
AB - This paper aims at presenting a detailed analysis of domestic air passengers behavior during a major air-traffic disturbance, from two complementary passenger-centric perspective: A passenger mobility perspective and a passenger social media perspective. By leveraging over 5 billion records of mobile phone location data per day from a major carrier in the United States, passenger mobility can be reliably analyzed, no matter which airline the passengers fly on or which airport they fly to and from. Such information is currently unavailable to the major aviation stakeholders at such scale and can be used to establish performance benchmarks from a passenger's perspective. Combining it with a Twitter analysis provides a more detailed and passenger-focused analysis than the traditional flight-centric measurements used to evaluate the overall system performance. More generally, these two passenger-centric analysis could be implemented in real-time for a daily evaluation of the Air Transportation System, enabling a faster analysis of the impact of major disruptions, whether due to meteorological conditions or system failures.
UR - https://ieeexplore.ieee.org/document/8637388/
UR - http://www.scopus.com/inward/record.url?scp=85062867407&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2018.00091
DO - 10.1109/ICDMW.2018.00091
M3 - Conference contribution
SN - 9781538692882
SP - 588
EP - 595
BT - IEEE International Conference on Data Mining Workshops, ICDMW
PB - IEEE Computer [email protected]
ER -