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Medientyp:
E-Artikel
Titel:
News Media Mining to Explore Speed-Crash-Traffic Association During COVID-19
Beteiligte:
Das, Subasish;
Sarkar, Sobhan
Erschienen:
SAGE Publications, 2022
Erschienen in:Transportation Research Record: Journal of the Transportation Research Board
Sprache:
Englisch
DOI:
10.1177/03611981221121261
ISSN:
0361-1981;
2169-4052
Entstehung:
Anmerkungen:
Beschreibung:
<jats:p> The COVID-19 pandemic has affected the lives of everyone from almost every perspective. Research communities from many domains have contributed to quantifying and mitigating the influence of the ongoing pandemic. The public depend on news media for reliable information. At the start of the pandemic in March 2020, many news media articles started to report on quieter roads resulting from travel restriction and work from home mandates, but also more excessive speeding and more traffic fatalities. Although the news media’s representation of the crash-speed association is often not based on data-driven safety analysis, the extent to which the media place emphasis on such news content has never been adequately quantified. The current study performed content analysis and text mining (both text network analysis and topic modeling) to explore the representations of speed-crash association in news media (local, national, and international) to provide insights into the generated news content. Findings reveal that topics such as a surge in fatal crashes, careless driving, driving under the influence, law enforcement, and equity issues, as well as impacts on pedestrians and bicyclists, were frequently highlighted by local, national, and international news media during the pandemic era. </jats:p>