A Computational Approach for Examining the Comparability of "Most-Viewed Lists" on Online News Sites. (March 2018)

• Record Type: Journal Article
• Authors: Zamith, Rodrigo
• Is Part Of: Journalism & mass communication quarterly. Volume 95:Number 1(2018:Mar.)
• Page Start: 122
• Page End: 141
• Publication Date: 2018-03
• Subjects: analytics -- metrics -- page views -- methodology -- computational content analysis; Journalism -- Periodicals; Mass media -- Periodicals; Communication -- Periodicals; Journalism -- United States -- Periodicals; Journalism -- Bibliography -- Periodicals; 070
• DOI: 10.1177/1077699017714223
• Languages: English
• ISSNs: 1077-6990

Abstract

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.