Expanding the Role of Trust in the Experience of Algorithmic Journalism
User Sensemaking of Algorithmic Heuristics in Korean Users
Bibliographic Data
| ID | 12909656 |
|---|---|
| Authors | Doh Shin (0000-0002-5439-4493, Zayed University, corresponding author) |
| Year | 2020 |
| Volume | 16 |
| Issue | 6 |
| Pages | 1168-1191 |
| Publication date | 2020-12-04 |
| 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 | 10.1080/17512786.2020.1841018 |
| OpenAlex | W3112876502 |
| Language | EN |
| Citations received | 24 |
| References cited | 40 |
Algorithmic journalism (AJ) has become widely popular, emerging in mainstream trends. Despite this surging popularity, little is known about the ways through which readers understand and actualize the potential for trust or affordances in AJ. The goal of the study is to highlight principles of algorithmic process in AJ and the processes these principles are perceived, appreciated and acted upon by AJ users. The idea of algorithmic trust is proposed as a new form of digital affordance in algorithm-driven news services. It identifies key issues of AJ and conceptualizes such issues in reference to algorithmic trust by analyzing how they influence reader satisfaction and adoption of AJ. A multi-mixed mixed method integrating interpretive methods and empirical survey was used for Korean users. Algorithmic affordances offer a useful standpoint on the conceptualization of algorithmic trust. Cognitive processes and heuristic mechanisms provide better foundations for algorithm design and development and a stronger basis for design of sensemaking AJ. Based on the study, a theoretical model is proposed to define algorithmic trust in the context of AJ
Affordance · Conceptualization · Context (archaeology · Empirical research · Epistemology · Heuristic · Heuristics · Human–computer interaction · Knowledge management · Mainstream · Political science · Popularity · Sensemaking · Computer Science · Ethics and Social Impacts of AI · Privacy, Security, and Data Protection · Psychology · Social Psychology · Virtual Reality Applications and Impacts · Artificial Intelligence
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| Unique citing works | 24 |
|---|---|
| Citations per year | 4 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 24 |