WASHINGTON, July 15 (Xinhua) -- Urban researchers from Massachusetts Institute of Technology (MIT) found the online restaurant data can help determine if a neighborhood would be a good place to live.
The study published on Monday in the Proceedings of the National Academy of Sciences showed that, in nine Chinese cities, the presence of restaurants could effectively predict a neighborhood's daytime and nighttime population, the number of businesses and overall spending.
A team led by Zheng Siqi, an urban studies professor at MIT, collected restaurant data from Dianping.com, the Chinese equivalent of Yelp, of Chinese cities including Beijing, Chengdu, Kunming and Zhengzhou.
Zheng's team matched the data to reliable, existing city data including aggregated mobile phone location data from 56.3 million people, band card records and company registration records.
They found that those data could predict 95 percent of the the variation in daytime and nighttime populations among neighborhoods, 93 percent of the variation in the number of businesses, and 90 percent of the variation in levels of consumer consumption, according to the study.
This is a more accurate proxy for estimating neighborhood-level population and economic activity than other methods previously used, like the satellite imaging of nighttime light.
In China, as in many other countries, a census is only taken once a decade, so it may be difficult to analyze the dynamics of a city's ever-changing areas on a faster-paced basis.
"Even without census data, we can predict a variety of a neighborhood's attributes, which is very valuable," said Zheng.
The researchers noted the correlations between restaurant landscape and neighborhood features did not specify an exact causal mechanism.
Sometimes restaurants can fill demand in already-thriving area, while at other times their presence is a harbinger of future development, according to Carlo Ratti, director of MIT's Senseable City Lab, and a co-author of the paper.
Zheng said that the model could also be applied to other Chinese cities and even globally.
