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Abusive and Hate speech Classification in Arabic Text Using Pre-trained Language Models and Data Augmentation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A new feature selection method based on frequent and associated itemsets for text classification
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T-HSAB: A Tunisian Hate Speech and Abusive Dataset
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Comparative Performance of Machine Learning and Deep Learning Algorithms for Arabic Hate Speech Detection in OSNs
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User Awareness of Privacy, Reporting System and Cyberbullying on Facebook
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Machine Learning for Hate Speech Detection in Arabic Social Media
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Towards Automatic Detection of Inappropriate Content in Multi-dialectic Arabic Text
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CNN-BiLSTM Model for Arabic Dialect Identification
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The effect of rebalancing techniques on the classification performance in cyberbullying datasets
inferredcites →https://doi.org/10.1007/s10579-023-09683-yopenalex-snapshot
Comparative performance of ensemble machine learning for Arabic cyberbullying and offensive language detection
inferredcites →https://doi.org/10.1007/s13369-021-05383-3openalex-snapshot
A Deep Learning Framework for Automatic Detection of Hate Speech Embedded in Arabic Tweets
inferredcites →https://doi.org/10.1007/s42979-022-01541-yopenalex-snapshot
TunBERT: Pretraining BERT for Tunisian Dialect Understanding
inferredcites →https://doi.org/10.1016/j.avb.2018.05.003openalex-snapshot
Hate speech review in the context of online social networks
inferredcites →https://doi.org/10.1016/j.chb.2018.08.039openalex-snapshot
Social media big data analytics: A survey
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Clustering-based spatial transfer learning for short-term ozone forecasting
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Business value of big data analytics: A systems-theoretic approach and empirical test
inferredcites →https://doi.org/10.1016/j.is.2021.101785openalex-snapshot
Multi-label Arabic text classification in Online Social Networks
inferredcites →https://doi.org/10.1016/j.jksuci.2015.02.003openalex-snapshot
Arabic text classification using Polynomial Networks
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A systematic literature review of Arabic dialect sentiment analysis
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Hate and offensive speech detection on Arabic social media
inferredcites →https://doi.org/10.1016/j.procs.2018.10.473openalex-snapshot
Dataset Construction for the Detection of Anti-Social Behaviour in Online Communication in Arabic
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Automatic Detection of Cyberbullying and Abusive Language in Arabic Content on Social Networks: A Survey
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Combining FastText and Glove Word Embedding for Offensive and Hate speech Text Detection
inferredcites →https://doi.org/10.1038/s41598-023-44113-7openalex-snapshot
Quantum computing and machine learning for Arabic language sentiment classification in social media
inferredcites →https://doi.org/10.1088/1742-6596/1032/1/012052openalex-snapshot
Arabic text classification using master-slaves technique
inferredcites →https://doi.org/10.1093/jeea/jvaa045openalex-snapshot
Fanning the Flames of Hate: Social Media and Hate Crime
inferredcites →https://doi.org/10.1108/ajim-10-2021-0293openalex-snapshot
Evaluating transfer learning approach for detecting Arabic anti-refugee/migrant speech on social media
inferredcites →https://doi.org/10.1109/aeect.2013.6716448openalex-snapshot
Arabic sentiment analysis: Lexicon-based and corpus-based
inferredcites →https://doi.org/10.1109/asonam.2018.8508247openalex-snapshot
Are they Our Brothers? Analysis and Detection of Religious Hate Speech in the Arabic Twittersphere
inferredcites →https://doi.org/10.1109/bigdata.2016.7841054openalex-snapshot
Word embeddings for Arabic sentiment analysis
inferredcites →https://doi.org/10.1109/csit.2016.7549465openalex-snapshot
A supervised approach for multi-label classification of Arabic news articles
inferredcites →https://doi.org/10.1109/iacs.2015.7103229openalex-snapshot
Scalable multi-label Arabic text classification
inferredcites →https://doi.org/10.1109/iccisci.2019.8716394openalex-snapshot
Sentiment Classifier: Logistic Regression for Arabic Services’ Reviews in Lebanon
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Language processing for arabic microblog retrieval
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Hate Speech Detection with Comment Embeddings
inferredcites →https://doi.org/10.1145/3041021.3054223openalex-snapshot
Deep Learning for Hate Speech Detection in Tweets
inferredcites →https://doi.org/10.1177/0165551520917651openalex-snapshot
Intelligent detection of hate speech in Arabic social network: A machine learning approach
inferredcites →https://doi.org/10.14257/ijmue.2015.10.4.21openalex-snapshot
A Lexicon-based Approach for Hate Speech Detection
inferredcites →https://doi.org/10.1609/aaai.v27i1.8539openalex-snapshot
Locate the Hate: Detecting Tweets against Blacks
inferredcites →https://doi.org/10.1609/icwsm.v11i1.14955openalex-snapshot
Automated Hate Speech Detection and the Problem of Offensive Language
inferredcites →https://doi.org/10.18653/v1/2020.semeval-1.271openalex-snapshot
KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media
inferredcites →https://doi.org/10.18653/v1/2021.acl-long.551openalex-snapshot
ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic
inferredcites →https://doi.org/10.18653/v1/2023.semeval-1.117openalex-snapshot
TeamAmpa at SemEval-2023 Task 3: Exploring Multilabel and Multilingual RoBERTa Models for Persuasion and Framing Detection
inferredcites →https://doi.org/10.18653/v1/d15-1299openalex-snapshot
ASTD: Arabic Sentiment Tweets Dataset
inferredcites →https://doi.org/10.18653/v1/d19-1474openalex-snapshot
Multilingual and Multi-Aspect Hate Speech Analysis
inferredcites →https://doi.org/10.18653/v1/n16-2013openalex-snapshot
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
inferredcites →https://doi.org/10.18653/v1/w17-2902openalex-snapshot
When does a compliment become sexist? Analysis and classification of ambivalent sexism using twitter data
inferredcites →https://doi.org/10.18653/v1/w17-3008openalex-snapshot
Abusive Language Detection on Arabic Social Media
inferredcites →https://doi.org/10.18653/v1/w19-3512openalex-snapshot
L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language
inferredcites →https://doi.org/10.18653/v1/w19-4604openalex-snapshot
Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects
inferredcites →https://doi.org/10.25046/aj020634openalex-snapshot
A Multilingual System for Cyberbullying Detection: Arabic Content Detection using Machine Learning
inferredcites →https://doi.org/10.3115/981574openalex-snapshot
Proceedings of the 31st annual meeting on Association for Computational Linguistics -
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Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.3390/app10238614openalex-snapshot
A Deep Learning Approach for Automatic Hate Speech Detection in the Saudi Twittersphere
inferredcites →https://doi.org/10.3390/bdcc7040170openalex-snapshot
Arabic Toxic Tweet Classification: Leveraging the AraBERT Model
inferredcites →https://doi.org/10.48550/arxiv.1310.4546openalex-snapshot
Distributed Representations of Words and Phrases and their Compositionality
inferredcites →https://doi.org/10.48550/arxiv.1901.07291openalex-snapshot
Cross-lingual Language Model Pretraining
inferredcites →https://doi.org/10.48550/arxiv.1906.08237openalex-snapshot
XLNet: Generalized Autoregressive Pretraining for Language Understanding
inferredcites →https://doi.org/10.5121/csit.2017.70401openalex-snapshot
Unsupervised Detection of Violent Content in Arabic Social Media
inferredcites →https://doi.org/10.5121/csit.2019.90208openalex-snapshot
DETECTION OF HATE SPEECH IN SOCIAL NETWORKS: A SURVEY ON MULTILINGUAL CORPUS
inferredcites →https://doi.org/10.7763/ijke.2015.v1.19openalex-snapshot
Detection of Abusive Accounts with Arabic Tweets
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Literature Review of Textual Cyber Abuse Detection Using Cutting‐Edge Natural Language Processing Techniques: Language Models and Large Language Models
inferred← citeshttps://doi.org/10.1007/978-3-031-80334-5_2openalex-snapshot
Machine Learning Approaches for Sentiment Analysis on Social Media
inferred← citeshttps://doi.org/10.1007/978-3-032-10929-3_38openalex-snapshot
Detection of Hate Speech on On-Line Social Platforms Using Machine Learning and Natural Language Processing – A Literature Review
inferred← citeshttps://doi.org/10.1007/978-3-032-30488-9_13openalex-snapshot
A Model Implementation to Detect Hate Speech Associated with Gender Violence by Natural Language Processing and Machine Learning
inferred← citeshttps://doi.org/10.1007/978-981-96-9248-4_41openalex-snapshot
Performance Assessment of Transformer Models on Algerian and Tunisian Arabic Hate Speech Tasks
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.115924openalex-snapshot
LLM-based text plus emoji multiclass hate speech language detection for resource constrained devices
inferred← citeshttps://doi.org/10.1080/1206212x.2026.2659937openalex-snapshot
Hybrid transformer-based approaches for suicidal posts detection
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A Novel Data Augmentation Framework for Arabic Multi-Label Text Classification Using AraBART, AraGPT2, and Borderline-SMOTE
inferred← citeshttps://doi.org/10.1109/ictcs65341.2025.10989442openalex-snapshot
Leveraging Contextualized and Word Embeddings for Arabic Hate Speech Detection
inferred← citeshttps://doi.org/10.1109/tcss.2026.3697248openalex-snapshot
DECNet: A Dual-Encoder Contrastive Model for Multilabel Detection of Hate and Abusive Speech in the Sudanese Vernacular
inferred← citeshttps://doi.org/10.1145/3758093openalex-snapshot
Fine-Grained Arabic Dialect Identification: Investigating Various Approaches Across Multiple Datasets
inferred← citeshttps://doi.org/10.2139/ssrn.5472934openalex-snapshot
A deep contrastive granular learning transformer for coarse-grained text representation
inferred← citeshttps://doi.org/10.3390/app15094941openalex-snapshot
A Comparative Evaluation of Transformers and Deep Learning Models for Arabic Meter Classification
inferred← citeshttps://doi.org/10.59743/jaf.v10i1.960openalex-snapshot
Data Augmentation Techniques for Arabic Short Text Processing
inferred← citeshttps://doi.org/10.7717/peerj-cs.2685openalex-snapshot
Data augmentation for Arabic text classification: a review of current methods, challenges and prospective directions
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