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Dual-Source Synthetic Uzbek Corpora for Sentiment Analysis and NER with Controlled Emoji Signals

Author

Listed:
  • Bobur Saidov

    (Faculty of Mechanics and Mathematics, Novosibirsk State University, 1 Pirogova str., Novosibirsk 630090, Russia)

  • Vladimir Barakhnin

    (Faculty of Mechanics and Mathematics, Novosibirsk State University, 1 Pirogova str., Novosibirsk 630090, Russia
    Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russia)

  • Shohrux Madirimov

    (Faculty of Mechanics and Mathematics, Novosibirsk State University, 1 Pirogova str., Novosibirsk 630090, Russia
    Tashkent Institute of Textile and Light Industry, Tashkent 100100, Uzbekistan)

  • Umid Ibragimov

    (Faculty of Mechanics and Mathematics, Novosibirsk State University, 1 Pirogova str., Novosibirsk 630090, Russia)

  • Shakhboz Meylikulov

    (Department of Information Technology and Exact Sciences, Termez University of Economics and Service, 38-B, Ibn-Sino str., Termez 190100, Uzbekistan)

  • Sultonbek Normamatov

    (Department of Computer Linguistics and Digital Technologies, Faculty of Social and Humanitarian Sciences, Alisher Navo′i Tashkent State University of Uzbek Language and Literature, 103, Yusuf Xos Khojib Str., Tashkent 100013, Uzbekistan)

  • Feruza Bahodirova

    (Department of Interfaculty Foreign Languages, Urgench State University, 14, Kh. Alimdjan str., Urgench 220100, Uzbekistan)

  • Javlonbek Matnazarov

    (Department of Language and Literature, Mamun University, 2, Bol-xovuz str., Khiva 220901, Uzbekistan)

  • Zarnigor Fayzullaeva

    (Department of Software Engineering, Tashkent University of Information Technologies Named After Muhammad al-Khwarizmi, Tashkent 100084, Uzbekistan)

Abstract

This data descriptor presents two fully synthetic corpora for sentiment analysis and named entity recognition (NER) in Uzbek. The first corpus contains 12,000 hybrid synthetic sentences generated from templates with lexical randomization, automatic insertion of named entities (PER/ORG/LOC), lexicon-based polarity scoring, and a controlled emoji distribution. The second corpus includes 3000 “manual-style” sentences designed to resemble short, naturally structured messages. Although the manual-style subset was initially intended to be emoji-free, the released version includes a 39.6% emoji presence (sentences containing at least one emoji) to maintain comparability in emotional markers across corpora. Both corpora are released in CSV, XLSX, and JSONL formats and share a unified schema (id, text, sentiment, entities, entity_type, polarity_score, polarity_source, token_count, emojis, emoji_position, emoji_sentiment, conflict_flag, sentiment_from_polarity_score, split). The dataset is publicly available via Mendeley Data (DOI: 10.17632/y2d5pcyrzz.3).

Suggested Citation

  • Bobur Saidov & Vladimir Barakhnin & Shohrux Madirimov & Umid Ibragimov & Shakhboz Meylikulov & Sultonbek Normamatov & Feruza Bahodirova & Javlonbek Matnazarov & Zarnigor Fayzullaeva, 2026. "Dual-Source Synthetic Uzbek Corpora for Sentiment Analysis and NER with Controlled Emoji Signals," Data, MDPI, vol. 11(2), pages 1-11, February.
    • Handle: RePEc:gam:jdataj:v:11:y:2026:i:2:p:28-:d:1854265
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