News Release

Crowdsourcing city complaints: Cornell Tech method improves equitability

Peer-Reviewed Publication

Cornell University

New York City, N.Y. - Crowdsourcing is an essential component of city management; crews can’t be everywhere at the same time, and they rely on residents to report issues to the proper authorities so they can be addressed. Researchers from Cornell Tech have developed a method to identify delays in the reporting of incidents such as downed trees and power lines, which could lead to practical insights and interventions for more equitable, efficient government service.

“The 311 system is a big one,” said Nikhil Garg, assistant professor of operations research and information engineering at Cornell Tech. “NYC gets over 3 million service requests a year from the public. For us, this started with a general question: Who is actually participating in all of these participatory mechanisms underlying government?”

The method, which works without knowing exactly when an incident occurred, uses the frequency of reports of the same incident by separate individuals to estimate how long it took for the incident to be first reported. The first report establishes that the incident occurred, and subsequent reports are used to establish the reporting rate. Applying their method to more than 1 million incident reports in New York City and Chicago, the researchers determined that a neighborhood’s socioeconomic characteristics are correlated with reporting rates.

Garg is senior author of “Quantifying Spatial Under-reporting Disparities in Resident Crowdsourcing,” which published Dec. 5 in Nature Computational Science.

“We’re optimistic that this method can be used to understand underreporting,” he said, “not just in 311 (citizen ‘hotline’) systems, but more broadly where these benchmark problems appear.”

Even after controlling for incident characteristics, such as the level of emergency response needed, they found that some neighborhoods reported incidents three times faster than others. This information could allow city managers to determine the reporting rates of different types of incidents in different neighborhoods, and address problems more equitably.

The disparities corresponded to socioeconomic characteristics of the neighborhoods. In New York City, reporting rates were positively correlated with higher population density; the fraction of people with college degrees; income; and the fraction of the population that is white.

“We find overwhelming evidence that people use 311 systems differently,” said Zhi Liu, lead student author and doctoral student. “And when we’re thinking about the downstream response to those reports, this can serve as a very good reference point. Say no one reports an incident and it’s been sitting there for a prolonged period: We might want to respond to it faster, so that the overall delay is similar across neighborhoods.”

This work was funded in part by the Urban Tech Hub at Cornell Tech.

For additional information, read this Cornell Chronicle story.

Cornell University has dedicated television and audio studios available for media interviews.

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