9 research outputs found
Beyond geotagged tweets: exploring the geolocalisation of tweets for transportation applications
Researchers in multiple disciplines have used Twitter to study various mobility
patterns and “live” aspects of cities. In the field of transportation planning, one
major area of interest has been to use Twitter data to infer movement patterns and
origins and destinations of trip-makers. In the area of transportation operations, researchers
have been interested in automated incident detection or event detection.
Because the number of geotagged tweets pinpointing the location of the user at the
time of tweeting tends to be sparse for transportation applications, there is a need to
consider expanding and geolocalising the sample of non-geotagged tweets that can
be associated with locations.We call this process “geolocalisation”. While geolocalisation
is an active area of research associated with the geospatial semanticWeb and
Geographic Information Retrieval, much of the work has focused on geolocalisation
of users, or on geolocalisation of tweeting activity to fairly coarse geographical
levels, whereas our work relates to street-level or even building-level geolocalisation.
We will consider two different approaches to geolocalisation that make use of
Points of Interest databases and a second information retrieval-based approach that
trains on geotagged tweets. Our objective is to make a comprehensive assessment
of the differences in spatial and content coverage between non-geotagged tweets
geolocalised using different approaches compared to using geotagged tweets alone.
We find that using geolocalised tweets allow discovery of a larger number of incidents
and socioeconomic patterns that are not evident from using geotagged data
alone, including activity throughout the metropolitan area, including deprived “Environmental Justice” (EJ) areas where the degree of social media activity detected
is usually low. Conclusions are drawn on the relative usefulness of the alternative
approaches