Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websites

Hans W. A. Hanley, Emily Okabe, Zakir Durumeric
1/15/2025
cs.SIcs.AIcs.CY

No official code found. Best implementation: hanshanley/tracking-takes (2 stars, Apache-2.0, last commit 2025-02-18).

Abstract

Understanding how misleading and outright false information enters news ecosystems remains a difficult challenge that requires tracking how narratives spread across thousands of fringe and mainstream news websites. To do this, we introduce a system that utilizes encoder-based large language models and zero-shot stance detection to scalably identify and track news narratives and their attitudes across over 4,000 factually unreliable, mixed-reliability, and factually reliable English-language news websites. Running our system over an 18 month period, we track the spread of 146K news stories. Using network-based interference via the NETINF algorithm, we show that the paths of news narratives and the stances of websites toward particular entities can be used to uncover slanted propaganda networks (e.g., anti-vaccine and anti-Ukraine) and to identify the most influential websites in spreading these attitudes in the broader news ecosystem. We hope that increased visibility into our distributed news ecosystem can help with the reporting and fact-checking of propaganda and disinformation.

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Code Implementations(1)

Apache-2.0

GitHub Repo for the USENIX 2025 paper Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websites

20Cython, PythonJan 2, 20251 years agoApache-2.0
llmsmisinformationnarrativesnetwork-analysisnews+1 more

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Cite this paper

@article{hanley2025tracking,
  title  = {Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websites},
  author = {Hans W. A. Hanley and Emily Okabe and Zakir Durumeric},
  year   = {2025},
  eprint = {2501.09102},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.09102v1}
}

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