Counter-messages as Prevention or Promotion of Extremism?! The Potential Role of YouTube
Bibliographic Data
| ID | 22693239 |
|---|---|
| Authors | Josephine B Schmitt (0000-0002-4689-3049, Chair for Communication and Media Psychology, University of Cologne, Germany, corresponding author), Diana Rieger (0000-0002-2417-0480, Institute for Media and Communication Studies, University of Mannheim, Germany), Olivia Rutkowski (Chair for Communication and Media Psychology, University of Cologne, Germany), Julian Ernst (0000-0002-1995-6390, Chair for Communication and Media Psychology, University of Cologne, Germany) |
| Year | 2018 |
| Volume | 68 |
| Issue | 4 |
| Pages | 780-808 |
| Publication date | 2018-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Communication (JOURNAL) |
| Journal identifiers | ISSN: 0021-9916 • E-ISSN: 1460-2466 |
| Publisher | Oxford University Press (OUP) (PUBLISHER) |
| DOI | 10.1093/joc/jqy029 |
| OpenAlex | W2809364268 |
| Language | EN |
| Citations received | 47 |
| References cited | 46 |
In order to serve as an antidote to extremist messages, counter-messages (CM) are placed in the same online environment as extremist content. Often, they are even tagged with similar keywords. Given that automated algorithms may define putative relationships between videos based on mutual topics, CM can appear directly linked to extremist content. This poses severe challenges for prevention programs using CM. This study investigates the extent to which algorithms influence the interrelatedness of counter- and extremist messages. By means of two exemplary information network analyses based on YouTube videos of two CM campaigns, we demonstrate that CM are closely—or even directly—connected to extremist content. The results hint at the problematic role of algorithms for prevention campaigns.
Advertising · Business · Content (measure theory) · Content analysis · Internet privacy · Order (exchange) · Political science · Politics · Promotion (chess) · Public relations · Sociology · Terrorism · Violent extremism · Computer Science · Hate Speech and Cyberbullying Detection · Law · Social Media and Politics · Terrorism, Counterterrorism, and Political Violence
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A Global Look at Time
| Unique citing works | 47 |
|---|---|
| Citations per year | 5,88 |
| Citation span | 2018 - 2026 (9) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 39 |