TY - GEN
T1 - Can social media data augment travel demand survey data?
AU - Chaniotakis, Emmanouil
AU - Antoniou, Constantinos
AU - Grau, Josep Maria Salanova
AU - Dimitriou, Loukas
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/22
Y1 - 2016/12/22
N2 - Travel surveys provide valuable inputs to a variety of models. While they are well-established, and reliable, they are also associated with large expenses (both in terms of time and actual cost). With the emergence of social media and alternative data sources, researchers and practitioners often wonder if such data sources can supplement (or obviate the need for) conventional data collection efforts. In this research, we empirically examine of the use of different social media data for such applications. Data from three popular Social Media is examined and compared with data from conventional travel-diary surveys for the city of Thessaloniki, Greece. Both spatial and temporal aspects of the activities' representation are considered. The findings of this research contribute towards the identification of methodologies that can support the inference of meaningful travel information from Social Media, which could in turn improve ITS applications.
AB - Travel surveys provide valuable inputs to a variety of models. While they are well-established, and reliable, they are also associated with large expenses (both in terms of time and actual cost). With the emergence of social media and alternative data sources, researchers and practitioners often wonder if such data sources can supplement (or obviate the need for) conventional data collection efforts. In this research, we empirically examine of the use of different social media data for such applications. Data from three popular Social Media is examined and compared with data from conventional travel-diary surveys for the city of Thessaloniki, Greece. Both spatial and temporal aspects of the activities' representation are considered. The findings of this research contribute towards the identification of methodologies that can support the inference of meaningful travel information from Social Media, which could in turn improve ITS applications.
UR - http://www.scopus.com/inward/record.url?scp=85010073637&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2016.7795778
DO - 10.1109/ITSC.2016.7795778
M3 - Conference contribution
AN - SCOPUS:85010073637
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 1642
EP - 1647
BT - 2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016
Y2 - 1 November 2016 through 4 November 2016
ER -