Algorithmic News Exposure is a scholarly construct within the field of news audience studies that denotes the process by which individuals encounter news content through personalized dissemination systems driven by computational algorithms, distinguishing it from non-algorithmic or human-curated news exposure mechanisms.
32
Publications
2.4K
Citations
71
Authors
50
Institutions
Publications per year
2017–2026
31
Parents
Publications
32
1–5 of 32
Authors
71
- DS
3
h-index
- LD
2
h-index
- CJ
2
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- KT
2
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- KV
2
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1–5 of 71
Institutions
50
Zayed University
Abu Dhabi, United Arab Emirates
3 h-index
3 publications
122 citations
Northwestern University
Evanston, United States
2 h-index
4 publications
160 citations
University of Oregon
Eugene, United States
2 h-index
3 publications
97 citations
Ghent University
Ghent, Belgium
2 h-index
10 publications
300 citations
Pace University
New York, United States
2 h-index
3 publications
121 citations
Pennsylvania State University
State College, United States
2 h-index
3 publications
166 citations
Michigan State University
East Lansing, United States
2 h-index
4 publications
1.2K citations
The University of Texas at Austin
Austin, United States
2 h-index
3 publications
62 citations
1–8 of 50
Venues
- Digital Journalism
6 publications · 260 citations
6
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- Computers in Human Behavior
4 publications · 370 citations
4
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- New Media & Society
3 publications · 90 citations
3
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- Social Media + Society
2 publications · 388 citations
2
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- Information Communication & Society
ICS · 2 publications · 545 citations
2
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1–5