# MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification

arXiv: https://arxiv.org/abs/2212.12061 · HTML: https://mlsanity.com/paper/2212.12061/

## 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 (most cited first, 9 of 9)

- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [Data and its (dis)contents: A survey of dataset development and use in machine learning research](https://mlsanity.com/paper/2012.05345/) (2020)
- [News Category Dataset](https://mlsanity.com/paper/2209.11429/) (2022)
- [NELA-GT-2020: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles](https://mlsanity.com/paper/2102.04567/) (2021)
- [NELA-GT-2018: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles](https://mlsanity.com/paper/1904.01546/) (2019)
- [Media Cloud: Massive Open Source Collection of Global News on the Open Web](https://mlsanity.com/paper/2104.03702/) (2021)
- [DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Tagging](https://mlsanity.com/paper/1707.04596/) (2017)
- [Quantifying Political Bias in News Articles](https://mlsanity.com/paper/2210.03404/) (2022)
- [RIPML: A Restricted Isometry Property based Approach to Multilabel Learning](https://mlsanity.com/paper/1702.05181/) (2017)

## Built on by (most cited first, 8 of 8)

- [A Survey on Large Language Model Acceleration based on KV Cache Management](https://mlsanity.com/paper/2412.19442/) (2024)
- [Text Clustering with Large Language Model Embeddings](https://mlsanity.com/paper/2403.15112/) (2024)
- [M4LE: A Multi-Ability Multi-Range Multi-Task Multi-Domain Long-Context Evaluation Benchmark for Large Language Models](https://mlsanity.com/paper/2310.19240/) (2023)
- [LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classification](https://mlsanity.com/paper/2411.19638/) (2024)
- [State of the Art in Text Classification for South Slavic Languages: Fine-Tuning or Prompting?](https://mlsanity.com/paper/2511.07989/) (2025)
- [LLM-Generated Negative News Headlines Dataset: Creation and Benchmarking Against Real Journalism](https://mlsanity.com/paper/2511.11591/) (2025)
- [SLeDGe: Semi-Supervised Learning on Data Streams with Graph Structure Learning](https://mlsanity.com/paper/2606.21096/) (2026)
- [Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering](https://mlsanity.com/paper/2607.10548/) (2026)

## 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.