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News Category Dataset

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arxiv 2209.11429 v3 pith:6JCZTVWO submitted 2022-09-23 cs.CL

classification cs.CL
keywords newsdatasetcategoryaroundauthenticvariousworldalong
verification ladder T0 review T1 audit T2 compute T3 formal
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People rely on news to know what is happening around the world and inform their daily lives. In today's world, when the proliferation of fake news is rampant, having a large-scale and high-quality source of authentic news articles with the published category information is valuable to learning authentic news' Natural Language syntax and semantics. As part of this work, we present a News Category Dataset that contains around 210k news headlines from the year 2012 to 2022 obtained from HuffPost, along with useful metadata to enable various NLP tasks. In this paper, we also produce some novel insights from the dataset and describe various existing and potential applications of our dataset.

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Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classification

    cs.LG 2025-09 conditional novelty 7.0 of 10

    EMCO oversamples minority text by estimating word-transition probabilities from both minority and majority documents, expanding the synthetic minority vocabulary.

  2. TI-StegoAlign: Channel-Guided Post-Training for Generative Text Steganography under Tokenization Inconsistency

    cs.CR 2026-08 conditional novelty 6.0 of 10

    A margin-supervision plus receiver-realistic preference post-training method achieves 100% receiver-side bit accuracy and 21.6% lower normalized perplexity deviation than the strongest baseline.

  3. MLego: Interactive and Scalable Topic Exploration Through Model Reuse

    cs.DB 2025-08 conditional novelty 6.0 of 10

    MLego reuses and merges materialized LDA models to answer ad-hoc topic queries quickly, using hierarchical plan search and batch reordering to keep the cost low.

  4. Political Leaning and Politicalness Classification of Texts

    cs.CL 2025-07 conditional novelty 6.0 of 10

    The authors compile large multi-dataset benchmarks for political leaning and politicalness classification, show that single-dataset models fail out-of-distribution, and release new models with improved cross-domain F1 scores.

  5. Dataset of News Articles with Provenance Metadata for Media Relevance Assessment

    cs.CL 2025-06 conditional novelty 6.0 of 10

    A new benchmark dataset and two tasks let researchers test whether AI systems can judge if a news image's recorded location and date match the article, with current chatbots scoring 64-81% on location but 42-58% on date.

  6. Investigating Algorithmic Bias in YouTube Shorts

    cs.SI 2025-07 reject novelty 4.0 of 10

    YouTube Shorts recommendations from political seeds drift to entertainment and positive-emotion content within the first few steps, with the drift unchanged by simulated watch-time.

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