The Multiple Facets of Influence
Identifying Political Influentials and Opinion Leaders on Twitter
Bibliographic Data
| ID | 4852029 |
|---|---|
| Authors | Elizabeth Dubois (0000-0003-1323-516X, University of Oxford, Oxford, UK), Devin Gaffney (0000-0002-9540-5814, Little Bird, Portland, OR, USA) |
| Year | 2014 |
| Volume | 58 |
| Issue | 10 |
| Pages | 1260-1277 |
| Publication date | 2014-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Behavioral Scientist (JOURNAL) |
| Journal identifiers | ISSN: 0002-7642 • E-ISSN: 1552-3381 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/0002764214527088 |
| OpenAlex | W1983403939 |
| Language | EN |
| Citations received | 126 |
| References cited | 30 |
This study compares six metrics commonly used to identify influential players in two of Canada's largest political Twitter communities based on the users, and ranking order of users, identified by each metric. All tweets containing the hashtag #CPC, representing the Conservative Party of Canada (government), and #NDP, representing the New Democratic Party of Canada (official opposition), were collected over a 2-week period in March 2013 and a follower network graph was created. Social network analysis and content analysis were employed to identify influentials. Kendall's τ was the primary quantitative measure for comparison. Categorization of Twitter profiles of users found within the top 20 most influential lists, according to each metric of influence, made up the qualitative portion of analysis. The authors find that measures of centrality-indegree and eigenvector centrality-identify the traditional political elite (media outlets, journalists, politicians) as influential, whereas measures considering the quality of messages and interactions provide a different group of influencers, including political commentators and bloggers. Finally, the authors investigate the possibility of using the local clustering coefficient of nodes to identify those who are both aware of the traditional elite and embedded in tightly knit communities, similar to the "opinion leader," described in the Two-Step Flow Hypothesis
Business · Categorization · Centrality · Democracy · Elite · Influencer marketing · Metric (unit) · Opposition (politics) · Political science · Politics · Social media · Social network analysis · Sociology · Statistics · World Wide Web · Artificial Intelligence · Complex Network Analysis Techniques · Computer Science · Law · Marketing · Mathematics · Opinion Dynamics and Social Influence · Social Media and Politics
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Articulación de la influencia en Twitter ante el anuncio de la Ley del referéndum en Cataluña
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Influencers, Amplifiers, and Icons
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Digital Public Sphere and Geography
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Who’s fuelling Twitter disinformation on the Covid-19 vaccination campaign? Evidence from a computational analysis of the green pass debate
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Please Follow Us
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Kanhaiya
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The Power of Social Networks
Intimate and Opinion-Oriented Communication? Examining Social Media Influencers’ Opinion Leader Potential Through Their Political Content
Communicative Antecedents of Political Persuasion
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Information Flow Within and Across Online Media Platforms
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Research Synthesis
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Collective dynamics of ‘small-world’ networks
Personal Influence
What the Hashtag
Content Analysis in Mass Communication
Getting the Message Out
The Fifth Estate in Internet Governance
Primary and secondary goals in the production of interpersonal influence messages
Real-Time Politics
Who Sets the Agenda
On the Importance of Marginality
The Political Information Cycle in a Hybrid News System
The Two-Step Flow of Communication
The Internet, Public Spheres, and Political Communication
Broadcasters and Hidden Influentials in Online Protest Diffusion
Imagining Twitter as an Imagined Community
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| Unique citing works | 126 |
|---|---|
| Citations per year | 11,45 |
| Citation span | 2015 - 2026 (12) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 118 |