To what extent does our online activity reveal who we are? Recent research has
demonstrated that the digital traces left by individuals as they browse and interact with …

This overview presents the framework and the results of the Author Profiling task at PAN
2016. The objective was to predict age and gender from a cross-genre perspective. For this …

Authorship analysis (AA) is the study of unveiling the hidden properties of authors from
textual data. It extracts an author's identity and sociolinguistic characteristics based on the …

Determining some demographics about the author of a document (eg, gender, age) has
attracted many studies during the last decade. To solve this author profiling task, various …

We present the results of gender and language variety identification performed on the tweet
corpus prepared for the PAN 2017 Author profiling shared task. Our approach consists of …

To determine author demographics of texts in social media such as Twitter, blogs, and
reviews, we use doc2vec document embeddings to train a logistic regression classifier. We …

The English language has, thus far, received the most attention in research concerning
automatic grammar error correction and detection. However, these tasks have been less …

Category suggestions or recommendations for customers or users have become an
essential feature for commerce or leisure websites. This is a growing topic that follows users' …

Author profiling is the computational task of inferring an author's demographics (eg, gender,
age etc.) based on text samples written by them. As in other text classification tasks, optimal …

One of the most popular topics that many researchers showed interest in recently is the
possibility of extracting the personal/demographic characteristics of the authors from their …