1,008
Views
6
CrossRef citations to date
0
Altmetric
Original Article

Characterizing Communication Patterns between Audiences and Newsbots

ORCID Icon & ORCID Icon
Pages 1093-1113 | Published online: 09 Oct 2020
 

Abstract

News organizations are increasingly exploring how the use of newsbots can enhance journalism by enabling novel ways to disseminate news and engage with audiences in social media environments. While newsbots have begun to draw attention in journalism studies, little consideration has been given to how audiences perceive and respond to newsbots. Through the lens of human–machine communication (HMC), this article presents a case study of a newsbot interacting with Twitter users who shared news articles from the New York Times (NYT). In particular, we analyzed the Twitter users’ perceptions and responses to the newsbot using qualitative analysis. We found that Twitter users perceived the newsbot in several degrees: from ignoring it, to addressing the content curated by the newsbot, to responding to newsbot itself. Moreover, we found that Twitter users offered a range of opinions, personal experiences, facts, counter-arguments, and affective displays when they addressed the content or the newsbot. We discuss how newsbots can be effective tools to enhance news engagement, the obstacles that they face when they interact in online environments, and reflect on the range of communicative roles that newsbots play with online audiences.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 104.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.