Creating an emotional dictionary: taking cultural-linguistic specifics into account

Abstract

This article presents a study on the creation of an emotional lexicon of the Uzbek language, taking into account its cultural and linguistic specificities. The emotional vocabulary of Uzbek reflects a complex interplay between language, national identity, and collective emotional experience. The purpose of the research is to develop a culturally sensitive framework for identifying and categorizing emotional expressions in Uzbek across diverse communicative contexts. The study analyzes a wide range of traditional sources, including folklore, proverbs, and classical literature, alongside modern discourse materials such as media texts, online forums, and social networks. Particular attention is given to dialectal variations and culturally embedded connotations, such as the double meaning of words like “achchiq” (bitter taste and emotional bitterness) and “suyanmoq” (physical leaning and emotional reliance). Methodologically, the research integrates corpus linguistics, sociolinguistic surveys, and AIbased sentiment analysis to ensure both empirical validity and cultural depth. As a result, the study proposes a prototype of an Uzbek emotional lexicon that captures emotional polarity, intensity, and contextual usage. The practical applications of this lexicon include improving human-computer interaction (e.g., chatbots), enriching language learning tools, and supporting sociolinguistic and affective computing research. The findings underscore the necessity of a standardized, culturally informed affective lexicon in Uzbek for preserving linguistic richness and enhancing emotional nuance in digital communication. This work contributes to the broader field of Turkic affective linguistics and emphasizes the importance of integrating cultural semantics into computational models.

More by Bobur Saidov

• Human-Reviewed Uzbek Legal Named Entity Recognition DatasetF1000Research · 2026
• UzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsJournal of Computer Science · 2026 · Citations: 3
• Entity-Aware Sentiment Analysis for Uzbek Social Media Using XLM-RoBERTa NER and LSTMUral Symposium on Biomedical Engineering, Radioelectronics and Information Technology · 2026
• Software System for Hybrid Sentiment Analysis of Uzbek Texts using Named EntitiesThe Herald of the Siberian State University of Telecommunications and Information Science · 2026