Don’t Quote me
Effects of Named, Quoted, and Partisan News Sources
Bibliographic Data
| ID | 12909446 |
|---|---|
| Authors | Megan Duncan (0000-0002-0547-2387, Virginia Tech), Kathleen Bartzen Culver (0000-0003-1651-3452, University of Wisconsin–Madison, corresponding author), Douglas M Mcleod (0000-0001-5808-2457, University of Wisconsin–Madison), Christopher Kremmer (0000-0002-1729-4354, UNSW Sydney) |
| Year | 2019 |
| Volume | 13 |
| Issue | 9 |
| Pages | 1128-1146 |
| Publication date | 2019-03-08 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journalism Practice (JOURNAL) |
| Journal identifiers | ISSN: 1751-2786 • E-ISSN: 1751-2794 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/17512786.2019.1588148 |
| OpenAlex | W2920889651 |
| Language | EN |
| Citations received | 9 |
| References cited | 28 |
Many news organizations have developed policies on the use of named and unnamed sources, including whether the latter can be directly quoted or paraphrased in news stories. In this experiment, we test how audience members respond to these policy dictates by measuring news credibility in a political story that manipulated whether the source was named, whether that source was directly quoted, and the source’s political connection to the story. We found that while each of these manipulations had little or no main effects, they combined to trigger a discernible change in credibility in the eyes of the audience
Advertising · Business · Credibility · Political science · Politics · Public relations · Source credibility · Test (biology · Electoral Systems and Political Participation · Law · Misinformation and Its Impacts · Social Media and Politics
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| Unique citing works | 9 |
|---|---|
| Citations per year | 1,5 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 9 |