Geolocation Prediction in Twitter

With ever increasing numbers of people interacting with social media, social data has become a gold mine of insights into the people, opinions and events of the world. Perhaps the greatest insights come when that data is partitioned into meaningful sub-populations, with one of the most obvious such dimensions being geographical. In many social platforms, however, geographical information is either missing, incomplete or not accessible. This greatly restricts the utility of social data for location-related applications such as regional sentiment analysis, local event detection, and geographically-bounded marketing and advertising. This shared task focuses on predicting geographical location (i.e., geotagging) using Twitter text data. The task on its own offers a benchmark dataset for comparing different geotagging methods, and also sheds light on how to expand geotagging from social media to a more general domain.