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.
The shared task will focus on English tweets. For both the user- and message-level tasks, you will be provided with compressed public Tweet JSON data sourced from the Twitter streaming API. Due to Twitter's terms of service, we can only provide tweet Ids and you are required to register a Twitter dev account to download data yourself. Downloader scripts will be provided.
Note: Author and co-author information shall be accompanied with submissions. An author can only join one team and each team can submit maximum 3 results for a level. The total number of co-author is maximum 5.
All submissions should conform to COLING 2016 style guidelines. Please remove author information from your papers, though ince this is a system description paper, if you are describing previously published work that is highly related, you don't need to make the references totally anonymous. The page limit is the same as the main workshop, 8 pages + 2 references, though you don't need to fill this, and four pages is fine if that's enough to describe your work.
Please submit your papers at https://www.softconf.com/coling2016/WNUT/, and select the track Geolocation Shared Task Papers.