100,000+ Movie Reviews from Kazakhstan: Russian, Kazakh, and Code-Switched Texts

• URL: http://arxiv.org/abs/2605.08600v2
• Date: Tue, 12 May 2026 03:18:44 GMT
• Title: 100,000+ Movie Reviews from Kazakhstan: Russian, Kazakh, and Code-Switched Texts
• Abstract summary: We present a new publicly available corpus of 100,502 movie reviews from Kazakhstan collected from kino.kz.<n>The dataset is multilingual, consisting mainly of Russian reviews alongside Kazakh and code-switched texts.<n>We define two sentiment tasks -- three-way polarity classification and five-class score classification -- and benchmark classical BoW/TF-IDF baselines against multilingual transformer models.
• Score: 2.2505457850833284
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a new publicly available corpus of 100,502 movie reviews from Kazakhstan collected from kino.kz, spanning 2001-2025 and covering 4,943 unique titles. The dataset is multilingual, consisting mainly of Russian reviews alongside Kazakh and code-switched texts. Reviews are manually annotated for language and sentiment polarity, and 11,309 reviews additionally contain explicit user-provided ratings. We define two sentiment tasks -- three-way polarity classification and five-class score classification -- and benchmark classical BoW/TF-IDF baselines against multilingual transformer models (mBERT, XLM-RoBERTa, RemBERT). Experimental results show that transformer models consistently outperform classical baselines on polarity classification, while score classification remains challenging under leakage-controlled evaluation due to severe class imbalance and subtle distinctions between adjacent rating levels.

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