MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification
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Abstract (arXiv)
This article presents a dataset of 10,917 news articles with hierarchical news categories collected between 1 January 2019 and 31 December 2019. We manually labeled the articles based on a hierarchical taxonomy with 17 first-level and 109 second-level categories. This dataset can be used to train machine learning models for automatically classifying news articles by topic. This dataset can be helpful for researchers working on news structuring, classification, and predicting future events based on released news.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 9 of its 29 references that are in the map. First posted on arXiv 22 Dec 2022.
Builds on
9 of 29 references.
References · 9
- 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307
- 2020Data and its (dis)contents: A survey of dataset development and use in machine learning researchcited by 260
- 2022News Category Datasetcited by 43
- 2021NELA-GT-2020: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articlescited by 29
- 2019NELA-GT-2018: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articlescited by 26
- 2021Media Cloud: Massive Open Source Collection of Global News on the Open Webcited by 20
- 2017DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Taggingcited by 5
- 2022Quantifying Political Bias in News Articlescited by 3
- 2017RIPML: A Restricted Isometry Property based Approach to Multilabel Learningcited by 1
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Citing papers per year: 2023: 1; 2024: 3; 2025: 2; 2026: 2.
8 papers.
- 2024A Survey on Large Language Model Acceleration based on KV Cache Managementcited by 131
- 2024Text Clustering with Large Language Model Embeddingscited by 27
- 2023M4LE: A Multi-Ability Multi-Range Multi-Task Multi-Domain Long-Context Evaluation Benchmark for Large Language Modelscited by 15
- 2024LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classificationcited by 6
- 2025State of the Art in Text Classification for South Slavic Languages: Fine-Tuning or Prompting?cited by 1
- 2025LLM-Generated Negative News Headlines Dataset: Creation and Benchmarking Against Real Journalismcited by 0
- 2026SLeDGe: Semi-Supervised Learning on Data Streams with Graph Structure Learningcited by 0
- 2026Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clusteringcited by 0
- 2026Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering12 Jul 2026
- 2026SLeDGe: Semi-Supervised Learning on Data Streams with Graph Structure Learning19 Jun 2026
- 2025State of the Art in Text Classification for South Slavic Languages: Fine-Tuning or Prompting?11 Nov 2025
- 2025LLM-Generated Negative News Headlines Dataset: Creation and Benchmarking Against Real Journalism24 Oct 2025
- 2024A Survey on Large Language Model Acceleration based on KV Cache Management27 Dec 2024
- 2024LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classification29 Nov 2024
- 2024Text Clustering with Large Language Model Embeddings22 Mar 2024
- 2023M4LE: A Multi-Ability Multi-Range Multi-Task Multi-Domain Long-Context Evaluation Benchmark for Large Language Models30 Oct 2023