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The Harvard Political Review reports that a Chicago nonprofit is scraping Twitter to pass on complaints about food poisoning in restaurants to the Chicago Department of Public Health:

Foodborne Chicago depends on human judgment in addition to computerized predictions. First, the algorithm "surfaces tweets that are related to foodborne illnesses." Next, "a human classifier goes through those complaints that the machine classifies, [...determining] what is really about food poisoning and what may be other noise." The Foodborne team then tweets back at the likely cases, providing a link for users to file an official complaint. In short, computers deal with the massive quantity of Twitter data, and humans ensure the quality of the result. According to its website, between its launch on March 23, 2013 and November 10, 2014, the Foodborne algorithm flagged 3,594 tweets as potential food poisoning cases. Of these tweets, human coders have identified 419, roughly 12 percent, as likely cases meriting a reply on Twitter.

But does it actually work?

In its first nine months of operation, Foodborne initiated 133 health inspections. Approximately 40 percent of these investigations uncovered critical or severe violations of the health code -- the kinds of violations that force restaurants to shut down or to remain open only under strict conditions. As Richardson noted, "that percentage is equivalent to the ... percentage of violations we find based on reports we get from 311" -- the phone number citizens can call to report food poisoning to their city’s municipal services. (...)

Apparently, yes.

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