User Engagement in Public Discourse on Genetically Modified Organisms
The Role of Opinion Leaders on Social Media
Dados Bibliográficos
| ID | 6219554 |
|---|---|
| Autores | Qian Xu (0000-0001-8130-0846, Elon University, Elon, NC, USA, autor correspondente), Nan Yu (0000-0001-6182-2268), Nan Sook Yu (0000-0002-5475-0718, University of Central Florida, Orlando, FL, USA), Y Song (0000-0001-5159-1689, Hong Kong Baptist University, Hong Kong SAR) |
| Ano | 2018 |
| Volume | 40 |
| Fascículo | 6 |
| Páginas | 691-717 |
| Data de publicação | 2018-12-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Science Communication (JOURNAL) |
| Identificadores do periódico | ISSN: 1075-5470 • E-ISSN: 1552-8545 |
| Editora | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/1075547018806526 |
| OpenAlex | W2898640731 |
| Idioma | EN |
| Citações recebidas | 21 |
| Referências citadas | 47 |
This study adopted a quantitative content analysis to examine how source attributes of opinion leaders and their message framing influenced user engagement in the public discourse of genetically modified organism (GMO) on Chinese social media. The findings showed that different source attributes and message frames used by opinion leaders varied in their respective influences on three dimensions of user engagement—reposts, comments, and likes. The attribute of account verification only predicted surface-level engagement (i.e., liking), whereas account type significantly influenced in-depth engagement (i.e., reposting and commenting). The fact, opportunity, pro-GMO, and international frames positively predicted user engagement
Biology · Opinion leadership · Organism · Political science · Politics · Public discourse · Public engagement · Public opinion · Public relations · Social media · Sociology · User engagement · World Wide Web · Climate Change Communication and Perception · Computer Science · Media Studies and Communication · Psychology · Social Media and Politics · Social Psychology · Genetics
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| Obras citantes distintas | 21 |
|---|---|
| Citações por ano | 3,5 |
| Intervalo de citações | 2020 - 2026 (7) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 21 |