When it came time to check their answers, the researchers identified a group of roughly 2,000 users to serve as a sort of ground truth. Finally, the tool looked for the time frame that appeared most often during the week and decided that the location with the most tweets in that time frame was most likely the person’s place of work. That gave the researchers a sense of whether the tweets might have been sent over the course of a typical eight-hour shift, even if that shift was overnight. LPAuditor analyzed the locations where users tweeted the most (not including home), then studied the time frames during which those tweets were sent. When it came to finding work locations, they did the opposite, analyzing tweet patterns during the week. The thinking was: During the week, you might tweet in the morning, at night, and on your day off, in an unpredictable pattern, but home is where most people spend the bulk of their time on weekends. Longest time span tweeting over the weekend. To predict which cluster might correspond to a user’s home, the researchers directed LPAuditor to look for locations where people spent the Jason Polakis, University of Illinois at Chicago "If you're not aware of the problem, you're never going to go remove that data." But the GPS data people shared before the update remains available through the API to this day. Now, users must opt-in to share their precise location-and, according to a Twitter spokesperson, a very small percentage of people do. Twitter didn't change this policy across its apps until April of 2015. But the GPS information would still be included in the tweet’s metadata and accessible through Twitter’s API. Users wouldn’t see the coordinates displayed on Twitter. For years, users who chose to geotag tweets with any location, even something as geographically broad as “New York City,” also automatically gave their precise GPS coordinates. The tool, called LPAuditor (short for Location Privacy Auditor), exploits what the researchers call an "invasive policy" Twitter deployed after it introduced the ability to tag tweets with a location in 2009. It can also predict where you work, where you pray, and other information you might rather keep private, like, say, whether you’ve frequented a certain strip club or gone to rehab. An international group of researchers has developed an algorithmic tool that uses Twitter to automatically predict exactly where you live in a matter of minutes, with more than 90 percent accuracy.
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