Recommendation System Effects
Recommendation System Effects is a theoretical construct that denotes the measurable influence of algorithmically generated suggestions on consumers' decision-making processes, behaviors, and preferences within online environments, distinguishing it from general user interface effects by its specificity to personalized or context-aware recommendation mechanisms.
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16.6K
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835
Authors
417
Institutions
Publications per year
2017–2026
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Parents
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iCoseg: Interactive co-segmentation with intelligent scribble guidance
Dhruv Batra, Adarsh Kowdle, Devi Parikh et al. · 2010 · 483 citations
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University of Minnesota
Minneapolis, United States
10 h-index
23 publications
3.6K citations
Decision Sciences (United States)
Fort Walton Beach, United States
7 h-index
11 publications
1.3K citations
University of Klagenfurt
Klagenfurt, Austria
7 h-index
8 publications
329 citations
KU Leuven
Leuven, Belgium
6 h-index
17 publications
1K citations

University of Glasgow
Glasgow, United Kingdom
5 h-index
8 publications
256 citations

University of British Columbia
Vancouver, Canada
5 h-index
7 publications
2.4K citations
Indiana University Bloomington
Bloomington, United States
4 h-index
4 publications
401 citations

Cornell University
Ithaca, United States
4 h-index
12 publications
1.3K citations
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Repository · 6 publications · 122 citations
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6 publications · 415 citations
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7 publications · 273 citations
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ISR · 5 publications · 481 citations
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5 publications · 923 citations
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