CoChat
Sign Up
Cited by 155Social Media and PoliticsNews Media Framing and Political CommunicationMedia and Digital Communication

The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.

Attention and amplification in the hybrid media system: The composition and activity of Donald Trump’s Twitter following during the 2016 presidential election

Zhang, Yini, Wells, Chris, Wang, Song, Rohe, Karl·2018·New Media & Society
DOI 10.1177/1461444817744390
Open this paper in CoChat — free account

Abstract

Building on studies of the hybrid media system and attention economy, we develop the concept of amplification to explore how the activities of social media–based publics may enlarge the attention paid to a given person or message. We apply the concept to the 2016 US election, asking who constituted Donald Trump’s enormous Twitter following and how that following contributed to his success at attracting attention, including from the mainstream press. Using spectral clustering based on social network similarity, we identify key publics that constituted Trump’s Twitter following and demonstrate how particular publics amplified his social media presence in different ways. Our discussion raises questions about how algorithms “read” metrics to guide content on social media platforms, how journalists draw on social media metrics in their determinations of news value and worthiness, and how the process of amplification relates to possibilities of citizen action through digital communication.

Overview

Integrity signals

Registry

Crossref · 10.1177/1461444817744390

Cites

63 of 63 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 63 references

Research works printed but not linked: 4

  1. Castells M, 2007, International Journal of Communication, 1, 238
  2. Gans HJ, 1979, Deciding What’s News: A Study of CBS Evening News, NBC Nightly News, Newsweek, and Times
  3. Gitlin T, 1980, The Whole World Is Watching: Mass Media in the Making & Unmaking of the New Left
  4. Qin T (2015) A Normalized and Regularized Nyström Extension for Clustering Network with General Degrees. Unpublished doctoral dissertation, University of Wisconsin Madison, Madison, WI.

Cited by

Sorted by citations

Items 101–153 of 153

Related

See all

Metadata

Authors
Zhang, Y., Wells, C., Wang, S., & Rohe, K.
Affiliations
University of Wisconsin–Madison (US)
Corresponding author
Zhang, Yini
ORCID
Venue
New Media & Society
Publisher
SAGE Publications
Published
2017-12-04
Volume
20
Issue
9
Pages
3161-3182
ISSN
  • 1461-4448 (ISSN-L)
  • 1461-7315
DOI
10.1177/1461444817744390
OpenAlex
W2773019705
Cited by
155
References
63
Citations by year
2026: 14 · 2025: 9 · 2024: 18 · 2023: 19 · 2022: 22 · 2021: 21 · 2020: 36 · 2019: 13 · 2018: 3
FWCI
33.09
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
New Media & Society (publishedVersion)
Topics
  • Social Sciences › Communication › Social Media and Politics
  • Social Sciences › Communication › News Media Framing and Political Communication
  • Social Sciences › Communication › Media and Digital Communication
Keywords
Donald Trump, Twitter followers, amplification, hybrid media system, attention economy, 2016 US presidential election, spectral clustering, social media metrics, news values, algorithmic curation, civic action

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