Automated Coding Systems
Automated Coding Systems is a methodological framework in data coding that employs algorithmic and machine-learning techniques to systematically categorize and annotate data without continuous human intervention, distinguishing it from manual or semi-automated approaches by its reliance on computational autonomy for scalable and consistent code application.
59
Publications
2.3K
Citations
207
Authors
92
Institutions
Publications per year
2017–2026
30
Parents
59
1–5 of 59
207
5
h-index
2
h-index
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University of California, Santa Barbara, United States
2 publications · 62 citations
2
h-index
2
h-index
1–5 of 207
92

Pennsylvania State University
State College, United States
5 h-index
10 publications
327 citations

University of Amsterdam
Amsterdam, The Netherlands
3 h-index
8 publications
170 citations
Virginia Tech
Blacksburg, United States
2 h-index
3 publications
71 citations
Netherlands Institute for the Study of Crime and Law Enforcement
Amsterdam, The Netherlands
2 h-index
11 publications
193 citations
Princeton University
Princeton, United States
2 h-index
4 publications
81 citations
University of California, Santa Barbara
Santa Barbara, United States
2 h-index
8 publications
256 citations

Tel Aviv University
Tel Aviv, Israel
2 h-index
6 publications
426 citations
University of Kansas
Lawrence, United States
2 h-index
2 publications
82 citations
1–8 of 92
3 publications · 59 citations
3
h-index
2 publications · 138 citations
2
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SSCR · 2 publications · 170 citations
2
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1 publications · 35 citations
1
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1 publications · 22 citations
1
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1–5