Work

Exploring transport perceptions in London: A twitter-based analysis by country of residence

Year: 2025
Type: article
Abstract: In an increasingly interconnected world, this study examines how geographical origin influences public sentiment toward transit systems, using social media as a lens. By analyzing a large dataset of tweets related to London's transit system, we explore differ-ences in sentiment between residents and visitors, including temporal patterns, as well as variations among visitors from different continents and countries. The results indicate that residents, who are more familiar with local transit issues, tend to express more negative sentiment than visitors (59.5% of residents vs. 56.8% of non-residents). Among visitors, sig-nificant differences emerge: Europeans exhibit the most negative sentiment, with their tweets being 1.7 times more likely to be negative than those of Asian visitors. Central and South Americans also show heightened negativity, while North Americans are only moder-ately more negative. Regarding temporal distribution, residents exhibit the highest levels of negative sentiment during early morning hours, likely due to commuting stress, while non-residents maintain consistent negativity throughout the day, peaking on weekends as they navigate the city. This highlights distinct temporal patterns in sentiment between these groups. From a continental perspective, North America has the second-highest number of negative tweets; however, it also has one of the lowest shares of complaints. Europeans and Asians primarily express confusion regarding COVID-19 regulations and punctuality is-sues. These findings underscore the importance of considering geographical and cultural contexts when analyzing public sentiment. They also offer actionable insights for policymak-ers and transit planners seeking to improve user satisfaction across diverse populations.
Authors: Martin Zajac, Jiří Horák, Joaquin Osorio -Arjona, Universidad Nacional de Educación a Distancia Facultad de Filosofía, Pavel Kukuliač
Language: English
Subfield: Transportation
Open Access status: diamond
OpenAlex ID: W4412473058
FWCI:
Cites: 39
Cited by:
Related to: 10