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natural-language-processing-9

Vietnamese Social Media Text Processing

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

A Large-scale Dataset for Hate Speech Detection on Vietnamese Social Media Texts

Kiet Van Nguyen, N. Nguyen, Son T. Luu•Sun Mar 21 2021

The ViHSD - a human-annotated dataset for automatically detecting hate speech on the social network, which contains over 30,000 comments and has one of three labels: CLEAN, OFFENSIVE, or HATE.

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Hate Speech Detection on Vietnamese Social Media Text using the Bidirectional-LSTM Model

Kiet Van Nguyen, N. Nguyen, A. Nguyen, Hang T. Do, H. D. Huynh•Fri Nov 08 2019

Bidirectional Long Short-Term Memory is used to build the model that can predict labels for social media text according to Clean, Offensive, Hate.

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Hate Speech Detection on Vietnamese Social Media Text using the Bi-GRU-LSTM-CNN Model

Kiet Van Nguyen, N. Nguyen, A. Nguyen, Duc-Vu Nguyen, T. Huynh•Fri Nov 08 2019

A deep learning method based on the Bi-GRU-LSTM-CNN classifier is implemented into the VLSP shared task 2019: Hate Speech Detection on Social Networks with the corpus which contains 20,345 human-labeled comments/posts for training and 5,086 for public-testing.

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Empirical Study of Text Augmentation on Social Media Text in Vietnamese

Kiet Van Nguyen, N. Nguyen, Son T. Luu•Thu Sep 24 2020

The data augmentation techniques are applied to solve the imbalance problem between classes of the dataset, increasing the prediction model's accuracy.

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Vietnamese hate and offensive detection using PhoBERT-CNN and social media streaming data

Kiet Van Nguyen, Phu Gia Hoang, Canh Duc Luu, K. Tran, An Trong Nguyen, Trong-Hop Do•Tue May 31 2022

An efficient pre-processing technique to clean comments collected from Vietnamese social media and a novel hate speech detection (HSD) model, which is the combination of a pre-trained PhoBERT model and a Text-CNN model, was proposed for solving tasks in Vietnamese.

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ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese

Kiet Van Nguyen, Chau-Thang Phan, Quoc-Nam Nguyen, Chi-Thanh Dang, Trong-Hop Do•Tue Sep 05 2023

This study presents a novel approach based on contextualized language model (PhoBERT) and graph-based method (Graph Convolutional Networks), ViCGCN, which jointly trained the power of Contextualized embeddings with the ability of GCN to capture more syntactic and semantic dependencies to address those drawbacks of imbalanced data and noisy data on social media.

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ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing

Duc-Vu Nguyen, Kiet Van Nguyen, Quoc-Nam Nguyen, Thang Chau Phan•Mon Oct 16 2023

The first monolingual pre-trained language model for Vietnamese social media texts, ViSoBERT, is presented, which is pre- trained on a large-scale corpus of high-quality and diverse Vietnamese socialMedia texts using XLM-R architecture and surpasses the previous state-of-the-art models on multiple Vietnamese social social media tasks.

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ViLexNorm: A Lexical Normalization Corpus for Vietnamese Social Media Text

Kiet Van Nguyen, Thanh-Nhi Nguyen, Thanh-Phong Le•Sun Jan 28 2024

This work introduces Vietnamese Lexical Normalization (ViLexNorm), the first-ever corpus developed for the Vietnamese lexical normalization task, which comprises over 10,000 pairs of sentences meticulously annotated by human annotators, sourced from public comments on Vietnam’s most popular social media platforms.

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Vietnamese Social Media Text Processing | State-of-the-Art