PAN16 Author Profiling

<p>We provide&nbsp;a training data set that consists of Twitter tweets in English, Spanish and Dutch.</p> <p>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.</p> <p><strong>Remark.</strong> Due to Twitter&#39;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&#39;s API. When we evaluate your software at our site, we do not expect it downloads tweets. We will do this beforehand.</p> <p>More information about the task:&nbsp;<a href="https://pan.webis.de/clef16/pan16-web/author-profiling.html">Link</a></p>