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

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.

Rodrigo Zamith

Associate Professor

My research and teaching interests lie at the intersection of journalism and technology, with a focus on the reconfiguration of journalism in a changing media environment and the development of digital research methods for social scientists.