Abstract
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.
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Notes
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https://pan.webis.de/index.html (last accessed 2018/05/21).
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Acknowledgment
Funding of the project “Identifying the Gender and Age of Online Chatters Using Formal Parameters of their Texts” from the Russian Science Foundation (no. 16-18-10050) is gratefully acknowledged.
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Litvinova, T., Sboev, A., Panicheva, P. (2018). Profiling the Age of Russian Bloggers. In: Ustalov, D., Filchenkov, A., Pivovarova, L., Žižka, J. (eds) Artificial Intelligence and Natural Language. AINL 2018. Communications in Computer and Information Science, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-030-01204-5_16
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