Conversations with Data: How Data Journalism Affects Online Comments in the New York Times

TL;DR

This study investigates how data journalism in The New York Times influences online comment interactions, showing that it increases user engagement through transparency and multimedia, thereby fostering democratic deliberation.

Contribution

It provides empirical evidence on the impact of data journalism on online user interactions and highlights the mediating role of statistical info, sources, and visualizations.

Findings

Data journalism correlates with increased user interactivity.

Statistical info and visualizations mediate user engagement.

Limited interactivity suggests only some users utilize data features.

Abstract

Users in the data age have access to more data than ever before, but little is known how they interact with it. Using transparency and multimedia, data journalism (DJ) lets users explore and interpret data on their own. This study examines how DJ affects online comments as a case study of user interactions with data. The corpus comprises 6,400 stories and their comment sections from the DJ and other sections of the New York Times, from 2014-2022. Results indicate that DJ is positively associated with higher level of interactivity between the users. This relationship is mediated by statistical information, information sources, and static visualizations. However, there is a low level of interactivity with the content; consequently, only part of the users use it. The results demonstrate how data accessibility through DJ engages the users in conversation. According to deliberation theory, this creates a conducive environment for democratic processes.