Scholar4AI Updated 2026-11-03 14:43 UTC+09:00

fake-news: papers linking to it

Kaggle · www.kaggle.com/competitions/fake-news

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to fake-news (https://www.kaggle.com/competitions/fake-news), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

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Key findings#

  • 5 papers in the tracked journals link to the Kaggle dataset fake-news in their Crossref records, the first in 2021; most of them (2) in 2021.
  • By category: AI (4) and Operations Research (1); the journals with the most are Cognitive Computation (2), Computers & Industrial Engineering (1) and Journal Of Big Data (1).
  • 2 of the papers build on one another: a later paper cites an earlier one that also links fake-news.

By year#

2021: 2 papers2022: 1 paper2024: 1 paper2025: 1 paper
20212025
Papers linking to fake-news by publication year
YearPapers
20212
20221
20241
20251

Journals#

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Papers linking to fake-news, most cited first
PublishedTitleJournalAuthorsCitationsLink
2021-04-07A temporal ensembling based semi-supervised ConvNet for the detection of fake news articlesExpert Systems with ApplicationsPriyanka Meel, Dinesh Kumar Vishwakarma81cites it
2022-07-09Linguistic features based framework for automatic fake news detectionComputers & Industrial EngineeringSonal Garg, Dilip Kumar Sharma68cites it
2021-10-18A Novel Visual-Textual Sentiment Analysis Framework for Social Media DataCognitive ComputationKanika Jindal, Rajni Aron17cites it
2024-03-19An adaptive hybrid african vultures-aquila optimizer with Xgb-Tree algorithm for fake news detectionJournal Of Big DataAmr A. Abd El-Mageed, Amr A. Abohany, Asmaa H. Ali et al.13cites it
2025-05-19Peeping into the Future: Understanding and Combating Generative AI-Based Fake NewsCognitive ComputationSanjeev Kumar, Siva Sai, Vinay Chamola et al.5cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). fake-news: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-fake-news

@misc{scholar4ai-code-kaggle-competition-fake-news,
  author = {{Scholar4AI}},
  title = {fake-news: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-competition-fake-news}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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