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

Autor:	Kantor, Avner, Rafaeli, Sheizaf
Rok vydání:	2024
Předmět:	Computer Science - Computers and Society Computer Science - Social and Information Networks
Druh dokumentu:	Working Paper
Popis:	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. Comment: Hawaii International Conference on System Sciences (HICSS)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2411.02045 Zobrazit plný text záznamu View this record from Arxiv