Daniel Schiff

43 papers receiving 1.0k citations

Daniel Schiff's Hit Papers

The impact of automation and artificial intelligence on worker well-being 2021 · 146 citations
1460+1+3Years since publication4080120

Peers

Daniel Schiff
Comparison fields: 5 of 120
  • Health Informatics 213
  • Safety Research 363
  • Computer Science Applications 167
  • Artificial Intelligence 247
  • Information Systems and Management 46
Replace Christine T. Wolf with:
Christine T. Wolf United States
Patrick Allo Belgium
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Patrice Chazerand United Kingdom
Robert Madelin Belgium
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Schiff

Since Specialization
Citations

This map shows the geographic impact of Daniel Schiff's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Schiff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Schiff more than expected).

Fields of papers citing papers by Daniel Schiff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Schiff. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Schiff. The network helps show where Daniel Schiff may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Schiff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Schiff Line = papers co-authored together Daniel Schiff links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021158
2 2020148
3
The impact of automation and artificial intelligence on worker well-being
Hit paper breakdown →
2021146
4 202085
5 202170
6 202165
7 202257
8 201955
9 202141
10 202432
11 202329
12 202023
13 202320
14 199616
15 202411
16
Teacher Networks in Philadelphia: Landscape, Engagement, and Value.
201510
17 201910
18 20249
19 20078
20 20237

About Daniel Schiff

Daniel Schiff is a scholar working on Safety Research, Sociology and Political Science, Artificial Intelligence, Political Science and International Relations and Information Systems, having authored 45 papers that have together received 1.1k indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (17 papers), Artificial Intelligence in Healthcare and Education (5 papers), Ethics in Business and Education (4 papers), Misinformation and Its Impacts (4 papers), Social Media and Politics (3 papers), Psychology of Moral and Emotional Judgment (3 papers), Policy Transfer and Learning (3 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Health Informatics (213 citations), Safety Research (363 citations), Computer Science Applications (167 citations), Artificial Intelligence (247 citations) and Information Systems and Management (46 citations). Daniel Schiff has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Jason Borenstein, Justin B. Biddle, Kelly Laas, Matthew O’Shaughnessy, Mark A. Davenport, Lav R. Varshney, Christopher J. Rozell, Claudia Nerdel, Arne Bewersdorff and Aladdin Ayesh. Their work appears in journals such as Computers and Education Artificial Intelligence, Policy and Society, American Political Science Review, Studies in Higher Education and Criminology & Public Policy.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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