The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Automation, Journalism, and Human–Machine Communication: Rethinking Roles and Relationships of Humans and Machines in News
Abstract
In this article, we argue that journalism studies, and particularly research focused on automated journalism, has much to learn from Human-Machine Communication (HMC), an emerging conceptual framework and empirically grounded research domain that has formed in response to the growing number of technologies—such as chatbots, social bots, and other communicative agents enabled by developments in artificial intelligence (AI)—that are designed to function as message sources, rather than as message channels. While the underlying, but often unquestioned, theoretical assumption in most communication research is that humans are communicators and machines are mediators, within HMC this assumption is challenged by asking what happens when a machine steps into this formerly human role. More than merely a semantic move, this theoretical reorientation opens up new questions about who or what constitutes a communicator, how social relationships are established through exchange among humans and machines, and what the resulting implications may be for self, society, and communication. In the particular case of automated journalism—in which software assumes a news-writing role that has long been considered a distinctly central, and indeed human, element of journalism—the introduction of HMC offers a generative starting point for theory development, advancing our understanding of humans, machines, and news for an oncoming era of AI technologies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Reassembling the Social: An Introduction to Actor-Network-Theory
Latour, B. (2005) · doi:10.1093/oso/9780199256044.001.0001 · Cited by 16,778
Domingo, D., Quandt, T., Heinonen, A., Paulussen, S., Singer, J. B., & Vujnovic, M. (2008) · Journalism Practice · doi:10.1080/17512780802281065 · Cited by 705
Carlson, M. (2015) · Digital Journalism · doi:10.1080/21670811.2014.976412 · Cited by 542
The “Concept” of Communication
Dance, F. E. X. (1970) · Journal of Communication · doi:10.1111/j.1460-2466.1970.tb00877.x · Cited by 211
Voices in and of the machine: Source orientation toward mobile virtual assistants
Guzman, A. L. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.08.009 · Cited by 199
Self-citationRobotic foot-in-the-door: Using sequential-request persuasive strategies in human-robot interaction
Lee, S. A., & Liang, Y. (. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.08.026 · Cited by 52
Cited by
Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm
Gambino, A., Fox, J., & Ratan, R. (2020) · Human-Machine Communication · doi:10.30658/hmc.1.5 · Cited by 626
“Thus, we employ the conceptualization of media agents to distinguish these entities from machines and technologies that are beyond the scope of CASA (see Guzman, 2018; Lewis et al., 2019, footnote 2).”
MethodSaif, N., Khan, S. U., Shaheen, I., ALotaibi, F. A., Alnfiai, M. M., & Arif, M. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2023.108097 · Cited by 301
Hermann, E. (2022) · New Media & Society · doi:10.1177/14614448211022702 · Cited by 214
Rizomyliotis, I., Kastanakis, M. N., Giovanis, A., Konstantoulaki, K., & Kostopoulos, I. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.08.035 · Cited by 85
Characterizing Communication Patterns between Audiences and Newsbots
Gómez-Zará, D., & Diakopoulos, N. (2020) · Digital Journalism · doi:10.1080/21670811.2020.1816485 · Cited by 15
Metadata
- Authors
- Lewis, S. C., Guzman, A. L., & Schmidt, T. R.
- Venue
- Digital Journalism
- Publisher
- Informa UK Limited
- Published
- 2019-04-21
- Volume
- 7
- Issue
- 4
- Pages
- 409-427
- ISSN
- 2167-0811 (ISSN-L)
- 2167-082X
- OpenAlex
- W2941957745
- Cited by
- 286
- References
- 6
- FWCI
- 62.24
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Automation, Journalism, and Human–Machine Communication: Rethinking Roles and Relationships of Humans and Machines in News. https://app.cochat.ai/papers/10.1080/21670811.2019.1577147
- The paper
- Lewis, S. C., Guzman, A. L., & Schmidt, T. R. (2019). Automation, Journalism, and Human–Machine Communication: Rethinking Roles and Relationships of Humans and Machines in News. Digital Journalism. https://doi.org/10.1080/21670811.2019.1577147
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.