The time and location data associated with the tweets were then presented to a group of 45 study participants, who were asked to try to deduce whether the tweets had originated at the Twitter users’ homes, workplaces, leisure destinations or commute locations.
Bottom line: They had little trouble figuring it out. Equipped with map-based representations, participants correctly identified Twitter users’ homes roughly 65 percent of the time and their workplaces at closer to 70 percent.
Part of a more general project at MIT’s Internet Policy Research Initiative, the paper was presented last week at the Association for Computing Machinery’s Conference on Human Factors in Computing Systems.
“Many people have this idea that only machine-learning techniques can discover interesting patterns in location data, and they feel secure that not everyone has the technical knowledge to do that,” said Ilaria Liccardi, a research scientist at MIT’s Internet Policy Research Initiative and first author on the paper. "What we wanted to show is that when you send location data as a secondary piece of information, it is extremely simple for people with very little technical knowledge to find out where you work or live.”
Twitter said it does not comment on third-party research, but directed users to online information about its optional location feature.
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