The winter is upon us and with it comes hashtags, like #snow and #weather, on Twitter.
That's the crux of a University at Buffalo study which examined how weather-related tweets can be analyzed to bolster computer models that, among other things, recommend safe driving speeds and which roads motorists should avoid during inclement weather.
"It doesn't matter if someone tweets about how beautiful the snow is or if they're complaining about unplowed roads.
Twitter users provide an unparalleled amount of hyperlocal data that we can use to improve our ability to direct traffic during snowstorms and adverse weather," said lead author Adel Sadek.
Traffic planners rely on models that analyze vehicular data from cameras and sensors, as well as weather data from nearby weather stations.
The approach works, however, its accuracy is limited because traffic and weather observations do not provide information on road surface conditions. For example, the model does not consider ice that lingers after a storm, or that snowplows have cleared a road.
Twitter can help address this limitation because its users often tweet about the weather and road surface conditions, and many opt to share their location via GPS.
Researchers found Twitter data to be more effective during the day (when more people tweet) and where the population is bigger (in the study's case, Buffalo has roughly five times more people than Niagara Falls, New York).
Researchers plan to continue improving their model by acquiring additional Twitter data for longer periods of time and at different locations.
The study is published in the journal Transportation Research Record.