Tweets Bring Better Weather Knowledge: Weather-Related Twitter Improves Models
Twitter is influencing the weather. Or rather, it is affecting how we are reacting to it and how well we know about it before we find ourselves in the midst of a snowstorm or gale-force winds, say.
A recent study by the University of Buffalo (UB) (a place aware of its snow predictions) took that a bit further and looked at the ways that analysis of weather-related tweets can boost the info in computer models that ultimately tell us which roads to take, how fast to drive on them, and other factors, according to a release.
"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," Adel Sadek, PhD and lead author of the study, of UB, in the release.
The study was published recently in the journal Transportation Research Record.
It's already the case that traffic planners source their information from models analyzing vehicular data from sensors and cameras, and weather-station data.
There are gaps, however -- for instance, the existing model doesn't take into consideration ice sticking around after a storm, or the conditions after a snowplow moves through the area, according to a statement.
The study looked at 360,000 or so tweets in the Buffalo Niagara area, from 19 days in December 2013. From those, they pulled about 3,000 relevant tweets that included words such as "snow" and "melt."
The data was then divided into "weather utterance" and "weather report" categories. If events reach a threshold of mentions within a certain time, they are designated as a "Twitter weather event." Using the tweets' geographic coordinates, the researchers were able to map the locations of inclement weather.
Within the tweet timing they saw a pattern: A snowfall means that weather-related tweets go up in number, vehicles travel more slow, and the volume of traffic on the road slowly decreases, as the statement noted.
When the Twitter data was inserted into an existing model of traffic and weather information, the new data increased the model's accuracy, said the release.
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