PAN16 Author Profiling
Creators
- 1. Universität Leipzig
- 2. Bauhaus-Universität Weimar
Description
We provide a training data set that consists of Twitter tweets in English, Spanish and Dutch.
The English and Spanish datasets are labeled with age and gender, whereas the Dutch one only with gender. With regard to age, we will consider the following classes: 18-24, 25-34, 35-49, 50-64, 65-xx.
Remark. Due to Twitter's privacy policy we cannot provide tweets directly, but only URLs referring to them. You will have to download them yourself. For your convenience, we provide a download software for this. We expect participants to extract gender and age information only from the textual part of a tweet and to discard any other meta information that may be provided by Twitter's API. When we evaluate your software at our site, we do not expect it downloads tweets. We will do this beforehand.
More information about the task: Link
Files
Additional details
References
- Francisco Rangel, Paolo Rosso, Ben Verhoeven, Walter Daelemans, Martin Potthast, and Benno Stein. Overview of the 4th Author Profiling Task at PAN 2016: Cross-Genre Evaluations. In Krisztian Balog, Linda Cappellato, Nicola Ferro, and Craig Macdonald, editors, CLEF 2016 Evaluation Labs and Workshop – Working Notes Papers, 5-8 September, Évora, Portugal, September 2016. CEUR-WS.org. ISSN 1613-0073.