Researchers use social media to track air pollution

According to the University of Wisconsin-Madison computer science
researchers, a method for using social
media posts to estimate air pollution levels with significant
accuracy has been developed.
Graduate students Shike Mei, Han Li and Jing Fan
analyzed Sina Weibo — a Twitter-like site that is China's
most popular social media outlet — to uncover real-time
information about air pollution levels in Chinese cities.
Though the approach cannot forecast future air quality, it
can provide accurate, real-time information on the Air
Quality Index (AQI).
For 30 days, the team monitored Weibo posts from 108
cities to see how often people complained about the air.
The group analyzed the text of the posts, as well as a time-
and-space correlation among cities and days, since
pollution flare-ups typically cover large amounts of
territory and can last for days.
Between 350,000 and 500,000 Chinese citizens die
prematurely each year because of air pollution, according
to the medical journal The Lancet. Even as smoking rates
decrease, lung cancer is on the rise. Yet, while large
Chinese cities have physical monitoring stations to gauge
air pollution levels, smaller cities generally do not due to
the expense of establishing and maintaining them.
For Mei, the project is more than just an intellectual exercise. In the area of central China where he grew up, there is
just one air quality monitoring station for an area where 60 million people live, he says.
"Anhui province, where I was born, is not very wealthy," Mei says. "There's not enough information about pollution,
and sometimes people suffer from heavier air pollution. We wondered, 'How can we use a new information source to
help people understand [the severity of] the pollution around?'"
The group's mathematical models did not use preselected keywords to analyze the text of Weibo posts. Rather, they
developed a machine learning model to assign different weights to different words used in the posts. The team's
approach to using publicly available data could be applied to a broad range of issues, says computer sciences
professor Jerry Zhu, who is working closely with the students, along with computer sciences professor Chuck Dyer.