Weighted Trilateration Using Domain Knowledge for Event Localization in Twitter Data

In this paper, we develop a novel approach called Domain Adapted Weighted Trilateration (DAWT). We use the idea of there are reference coordinates at known locations that scrape the microblog (tweet) counts in time and space (circular regions around the reference coordinate). The change in counts of tweets would be indicative of an event pattern. We propose the use of DAWT to combine the information from multiple reference points to find the exact location of the event. We propse the use of domain knowledge in the form of counts of tweet or spatial relationship between reference points to calculate the weights for trilateration. We use microblogging data collected from Twitter to evaluate our model and compare it with other baseline methods.