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The paper discusses challenges in exploiting geotagged social media posts (such as Instagram images) for purposes of target (event) tracking. The argument for social media exploitation for tracking lies in that physical events, such as protests, acts of terror, or natural disasters elicit a response on social media in the neighborhood of the event. However, the density of social media posts is proportional to the local population density. Hence, inferred event locations based on the ensuing distribution of posts are skewed by disparities in population density around the true event location. The paper describes an unsupervised approach to neutralize the effect of uneven population density. Evaluation using Instagram footprints of recent events shows that the approach leads to a much more accurate estimation of real event trajectories.
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