Year: 2026
Type: preprint
Abstract: UzEDSA is an annotated corpus for emotion detection and sentiment analysis in Uzbek social media comments. It contains 304,364 unique comments after batch merging, invalid-record removal, and duplicate filtering. Each comment is labelled with a multi-attribute schema covering primary emotion, multi-emotion annotation, sentiment polarity, emotional intensity, sarcasm, and domain. The emotion inventory includes JOY, SAD, ANG, FEA, SUR, TRU, DIS, ANT, MIX, and NEU. The corpus preserves social media features such as spelling variation, Uzbek Latin-Cyrillic script mixing, Uzbek-Russian code-switching, emojis, slang, repeated characters, markup artifacts, short reactions, and long comments. It covers general, personal, news, technology, medical, education, transport, service, and marketing domains. This Data Descriptor documents corpus construction, preprocessing, annotation, deduplication, validation, repository records, and usage notes. UzEDSA supports reusable research on low-resource Uzbek affective NLP, including emotion classification, polarity classification, intensity prediction, sarcasm-aware modelling, domain adaptation, and corpus-based analysis.
Source: Research Square
Authors: Botir Elov, Alayev Ruhillo, Zilola Xusainova
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7160315086