Assessing the Markup Layer in U.S.-Based Digital News Publishing

Media and Society
Written By Alexis Avedisian

Video

Team Information

Team Members

  • Susan McGregor, Associate Research Scholar, Data Science Institute, Columbia University

  • Contributing Students:

  • Bernat Ivancsics, Columbia University

  • Eve Washington, Columbia University

  • Helen Yang, Columbia University

  • Emily Sidnam-Mauch, Clemson University

  • Ayana Monroe, UNC Chapel Hill

  • Errol Francis II, Clemson University

  • Joseph Bonneau, New York University

  • Kelly Caine, Clemson University

Abstract

By extracting, analyzing, and comparing the markup layer of a corpus of 2,226 digital news stories gathered from the main pages of 742 national, local, Black, and other identity-based news organizations, this research illustrates the broad extent to which news publishers continuously grapple with platform-driven markup requirements, even as the robustness of the markup content provided varies dramatically according to the scale of the news organization and the communities served. In particular, this work assesses Schema.org’s inventory of ascribed metadata fields, as well as Facebook and Twitter’s proprietary metadata annotations. Through this study we identify existing publishing practices and map various markup strategies that allow news stories to be “read,” ranked, and distributed by curation algorithms that ultimately shape news organizations’ participation in the wider platform economy of digital content distribution.

Team Lead Contact

Susan McGregor: sem2196@columbia.edu

Alexis Avedisian
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