Unveiling the effect of social media communication on urban mobility

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Conventional methods to understand urban transportation mode choice primarily revolve
around assessing the relation costs/benefts among the diferent mobility alternatives.
However, emerging research has emphasized the signifcance of comprehending intricate
social processes that shape decision-making in urban mobility. This study delves into the
impact of social networks on aggregated travel behavior, using a comprehensive dataset
encompassing multiple data sources such as Twitter/X messages, bicycle sharing system
(BSS) and trafc counts, weather and socio-demographic information. Focusing specifcally
on the city of Madrid, Spain, the dataset covers an extensive period, capturing daily data
from 2018 to 2021. To gain deeper insights into the underlying infuences, a combination
of panel regression models and a topic modeling approach were employed for analysis.
The study’s fndings highlight the signifcant impact of social media communication on
transportation behavior, revealing a positive correlation between higher social media
message volume and increased usage of public and sustainable transportation options like
subways and BSS, while private car usage decreased. Although there is message salience,
i.e., a sudden surge in tweet numbers leads to a temporary shift in behavior, the fndings
suggest that municipalities can efectively infuence transportation behavior by strategically
communicating messages related to sustainable transportation through social networks