Location Mention Detection in Tweets and Microblogs

The automatic identification of location expressions in social media text is an actively researched task. We present a novel approach to detection mentions of locations in the texts of microblogs and social media. We propose an approach based on Noun Phrase extraction and n-gram based matching instead of the traditional methods using Named Entity Recognition (NER) or Conditional Random Fields (CRF), arguing that our method is better suited to noisy microblog text. Our proposed system is comprised of several individual modules to detect addresses, Points of Interest (e.g. hospitals or universities), distance and direction markers; and location names (e.g. suburbs or countries). Our system won the ALTA 2014 Twitter Location Detection shared task with an F-score of 0.792 for detecting location expressions in a test set of 1,000 tweets, demonstrating its efficacy for this task. A number of directions for future work are discussed. Keywords-location; detection; identification; Twitter; tweet; microblog; social media;