# Emotion Recognition for Vietnamese Social Media Text

arXiv: https://arxiv.org/abs/1911.09339 · HTML: https://mlsanity.com/paper/1911.09339/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2019.

## Built on by (most cited first, 23 of 23)

- [The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset](https://mlsanity.com/paper/2303.03915/) (2023)
- [Constructive and Toxic Speech Detection for Open-domain Social Media Comments in Vietnamese](https://mlsanity.com/paper/2103.10069/) (2021)
- [SA2SL: From Aspect-Based Sentiment Analysis to Social Listening System for Business Intelligence](https://mlsanity.com/paper/2105.15079/) (2021)
- [ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing](https://mlsanity.com/paper/2310.11166/) (2023)
- [VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding](https://mlsanity.com/paper/2403.15882/) (2024)
- [SMTCE: A Social Media Text Classification Evaluation Benchmark and BERTology Models for Vietnamese](https://mlsanity.com/paper/2209.10482/) (2022)
- [Crossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models](https://mlsanity.com/paper/2403.02715/) (2024)
- [Vietnamese Complaint Detection on E-Commerce Websites](https://mlsanity.com/paper/2104.11969/) (2021)
- [The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages](https://mlsanity.com/paper/2310.14557/) (2023)
- [SailCompass: Towards Reproducible and Robust Evaluation for Southeast Asian Languages](https://mlsanity.com/paper/2412.01186/) (2024)
- [Improving Sentiment Analysis By Emotion Lexicon Approach on Vietnamese Texts](https://mlsanity.com/paper/2210.02063/) (2022)
- [SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?](https://mlsanity.com/paper/2508.12243/) (2025)
- [Span Detection for Aspect-Based Sentiment Analysis in Vietnamese](https://mlsanity.com/paper/2110.07833/) (2021)
- [ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese](https://mlsanity.com/paper/2309.02902/) (2023)
- [ViLexNorm: A Lexical Normalization Corpus for Vietnamese Social Media Text](https://mlsanity.com/paper/2401.16403/) (2024)
- [A Weakly Supervised Data Labeling Framework for Machine Lexical Normalization in Vietnamese Social Media](https://mlsanity.com/paper/2409.20467/) (2024)
- [Advancing Vietnamese Information Retrieval with Learning Objective and Benchmark](https://mlsanity.com/paper/2503.07470/) (2025)
- [Is word segmentation necessary for Vietnamese sentiment classification?](https://mlsanity.com/paper/2301.00418/) (2023)
- [New Benchmark Dataset and Fine-Grained Cross-Modal Fusion Framework for Vietnamese Multimodal Aspect-Category Sentiment Analysis](https://mlsanity.com/paper/2405.00543/) (2024)
- [ViGoEmotions: A Benchmark Dataset For Fine-grained Emotion Detection on Vietnamese Texts](https://mlsanity.com/paper/2602.08371/) (2026)
- [VIVID: A Culturally Grounded Benchmark Exposing the Figurative Language Gap in Vietnamese NLP](https://mlsanity.com/paper/2608.03095/) (2026)
- [How Robust Are LLMs to Vietnamese Dialects?](https://mlsanity.com/paper/2608.10414/) (2026)
- [ViTOED: A Dataset for Target-Oriented Emotion Detection on Vietnamese Social Media Texts](https://mlsanity.com/paper/2608.12776/) (2026)

## Abstract (arXiv)

Emotion recognition or emotion prediction is a higher approach or a special case of sentiment analysis. In this task, the result is not produced in terms of either polarity: positive or negative or in the form of rating (from 1 to 5) but of a more detailed level of analysis in which the results are depicted in more expressions like sadness, enjoyment, anger, disgust, fear, and surprise. Emotion recognition plays a critical role in measuring the brand value of a product by recognizing specific emotions of customers' comments. In this study, we have achieved two targets. First and foremost, we built a standard Vietnamese Social Media Emotion Corpus (UIT-VSMEC) with exactly 6,927 emotion-annotated sentences, contributing to emotion recognition research in Vietnamese which is a low-resource language in natural language processing (NLP). Secondly, we assessed and measured machine learning and deep neural network models on our UIT-VSMEC corpus. As a result, the CNN model achieved the highest performance with the weighted F1-score of 59.74%. Our corpus is available at our research website.