A Computational Approach for Examining the Comparability of “Most-Viewed Lists” on Online News Sites

Bibliographic Data

ID7499951
AuthorsRodrigo Zamith (0000-0001-8114-1734, University of Massachusetts Amherst, corresponding author)
Year2017
Volume95
Issue1
Pages122-141
Publication date2017-07-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournalism & Mass Communication Quarterly (JOURNAL)
Journal identifiersISSN: 1077-6990 • E-ISSN: 2161-430X
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/1077699017714223
OpenAlexW2750770654
LanguageEN
Citations received3
References cited40

This study introduces a computational approach for evaluating the lists of most-viewed items present on the homepages of many news organizations, focusing on two dimensions: the list’s rate of change over the course of the day and the median time it takes a news item to appear on the list. That approach is then applied in an analysis of 21 news organizations over 2 months, revealing clusters across those dimensions which indicate the reporting of different data. Scholars are ultimately encouraged to perform their own analyses and cautioned against assuming the lists are comparable just because they appear alike

Comparability · Data science · Information retrieval · World Wide Web · Complex Network Analysis Techniques · Computer Science · Mathematics · Media Studies and Communication · Social Media and Politics

Tools

Open DOISci-Hub