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problems early or in their entirety through those channels because subscribers typically do not call a call center until they are certain the problem was caused by a network. In this paper, we discuss a way to monitor a social networking service (SNS) (Twitter in particular) to find out about problems that affect subscribers
tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center of the event location. We regard each Twitter user as a sensor and apply particle filtering, which are widely used for
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