Profiling the Age of Russian Bloggers

P. 167–177.

Litvinova T., Sboev A., Panicheva P.

The task of predicting demographics of social media users, bloggers and authors of other types of online texts is crucial for marketing, security, etc. However, most of the papers in authorship profiling deal with author gender prediction. In addition, most of the studies are performed in English-language corpora and very little work in the area in the Russian language. Filling this gap will elaborate on the multi-lingual insights into age-specific linguistic features and will provide a crucial step towards online security management in social networks. We present the first age-annotated dataset in Russian. The dataset contains blogs of 1260 authors from LiveJournal and is balanced against both age group and gender of the author. We perform age classification experiments (for age groups 20–30, 30–40, 40–50) with the presented data using basic linguistic features (lemmas, part-of-speech unigrams and bigrams etc.) and obtain a considerable baseline in age classification for Russian. We also consider age as a continuous variable and build regression models to predict age. Finally, we analyze significant features and provide interpretation where possible.

Keywords: text classification, author profiling, age prediction

In book

Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, Proceedings

Issue 930. , Switzerland: Springer, 2018.