David T. Smith

1.1k citations
61 papers · 609 indexed · h-index 16

David T. Smith

47 papers receiving 554 citations

Peers

David T. Smith
Comparison fields: 5 of 116
  • Health 163
  • Computer Science Applications 54
  • Modeling and Simulation 31
  • Sociology and Political Science 160
  • Infectious Diseases 61
Replace Cristina Pulido with:
Cristina Pulido Spain
Elizabeth Buchanan United States
Christofer Edling Sweden
Per Engzell Sweden
Emmanuel Koku United States
A. G. Howson United States
Francesc Saigí-Rubió Spain
Arun Frey United Kingdom
Joachim Allgaier Germany
Peter Washer United Kingdom
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Citations per year

Countries citing papers authored by David T. Smith

Since Specialization
Citations

This map shows the geographic impact of David T. Smith'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 David T. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Smith more than expected).

Fields of papers citing papers by David T. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David T. Smith. 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 David T. Smith. The network helps show where David T. Smith may publish in the future.

Co-authorship network

The 25 scholars most cited alongside David T. Smith, 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 David T. Smith Line = papers co-authored together David T. Smith links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20199
3 20192
4 20180
5 201853
6 20171
7 201715
8 201524
9 20141
10
Comparing Students Performance in Online versus Face-to-Face Courses in Computer Literacy Courses
20144
11 201433
12 20131
13
A formal concept analysis approach to association rule mining: the quicl algorithms
20091
14 20077
15 198424
16
You Can Grow Out of Burnout.
19810
17 19818
18 19724
19 19714
20
The Statute of Uses: A Look at Its Historical Evolution and Demise
19661

About David T. Smith

David T. Smith is a scholar working on Computer Science Applications, Health, Business and International Management, Media Technology and Political Science and International Relations, having authored 61 papers that have together received 609 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (8 papers), Religion and Society Interactions (7 papers), American Constitutional Law and Politics (7 papers), Information Systems Education and Curriculum Development (6 papers), Sensor Technology and Measurement Systems (4 papers), Teaching and Learning Programming (4 papers), Mormonism, Religion, and History (3 papers) and Online and Blended Learning (3 papers). The work is most often cited by research in Health (163 citations), Computer Science Applications (54 citations), Modeling and Simulation (31 citations), Sociology and Political Science (160 citations) and Infectious Diseases (61 citations). David T. Smith has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Azad Ali, Katie Attwell, Uwana Evers, Paul Ward, A. M. Glazer, Paul D. Groves, David J. Rogers, Stephen Chaudoin, Zhiyue Zheng and Sridhar Idapalapati. Their work appears in journals such as Journal of Information Technology Education Innovations in Practice, Vaccine, Politics, PS Political Science & Politics and Bulletin of Entomological Research.

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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