Estimating Travel Demand from Twitter using an Individual Mobility Model: In Sweden, The Netherlands and São Paulo
Typ
Examensarbete för masterexamen
Program
Publicerad
2020
Författare
EK, KRISTOFFER
WENNERBERG, ERIC
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The cost of conducting household travel surveys is increasing, while the response
rate is decreasing, pushing researchers to explore new sources of data that can be
used to estimate travel demand. Among these new data sources is geotagged tweets
from Twitter due to its large quantity of available data and low cost of access. At
the same time, using Twitter for travel demand estimation has garnered criticism
regarding the biases inherent in Twitter data. This thesis uses geotagged tweets
from three regions: Sweden, the Netherlands and São Paulo, to quantify the bias in
Twitter data and develop a novel model that estimates travel demand by de-biasing
the raw Twitter data. The model integrates two natural dimensions of individual
mobility: regularly returning to habitual locations and occasionally exploring
new locations. The proposed model addresses the under-representation of habitual
places such as home and workplace and corrects the geotagging behavioural bias
of overly representing long-distance travel. The model is validated against external
data sources in each of the three regions and it is found to result in significant improvements
over contemporary methods for using Twitter data for travel demand
estimation. The model’s parameters are robust across regions studied, and by using
the parameters found in this thesis one can expect the same improvements compared
to contemporary approaches when applied to other regions.
Beskrivning
Ämne/nyckelord
human mobility , travel demand estimation , Twitter , ndividual mobility model