Michael Ann DeVito

1.9k citations
36 papers · 1.3k · h-index 14

Impact in

Papers in

Michael Ann DeVito

32 papers receiving 1.3k citations

Peers

Michael Ann DeVito
Comparison fields: 5 of 95
  • Communication 402
  • Human-Computer Interaction 265
  • Safety Research 234
  • Computer Science Applications 106
  • Sociology and Political Science 734
Replace Morgan Klaus Scheuerman with:
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Citations per field
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Citations per year

Countries citing papers authored by Michael Ann DeVito

Since Specialization
Citations

This map shows the geographic impact of Michael Ann DeVito'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 Michael Ann DeVito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Ann DeVito more than expected).

Fields of papers citing papers by Michael Ann DeVito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Ann DeVito. 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 Michael Ann DeVito. The network helps show where Michael Ann DeVito may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016187
2 2017171
3 2018152
4 2017145
5 2018143
6 202175
7 202269
8 202060
9 202355
10 201953
11 202131
12 201931
13 201818
14 202014
15 202313
16 202112
17 202212
18 202011
19 20239
20 20216

About Michael Ann DeVito

Michael Ann DeVito is a scholar working on Sociology and Political Science, Communication, Clinical Psychology, Human-Computer Interaction and Artificial Intelligence, having authored 36 papers that have together received 1.3k indexed citations. Recurring topics across this work include Social Media and Politics (11 papers), Sexuality, Behavior, and Technology (10 papers), Impact of Technology on Adolescents (9 papers), Innovative Human-Technology Interaction (9 papers), Privacy, Security, and Data Protection (7 papers), Hate Speech and Cyberbullying Detection (7 papers), Digital Games and Media (5 papers) and Ethics and Social Impacts of AI (5 papers). The work is most often cited by research in Communication (402 citations), Human-Computer Interaction (265 citations), Safety Research (234 citations), Computer Science Applications (106 citations) and Sociology and Political Science (734 citations). Michael Ann DeVito has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Jeremy Birnholtz, Ashley Marie Walker, Jeffrey T. Hancock, Darren Gergle, Megan French, Stevie Chancellor, Jed R. Brubaker, Katta Spiel, Alex A. Ahmed and Jennifer A. Rode. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Digital Journalism, ACM Transactions on Computer-Human Interaction, International Journal of Pediatric Otorhinolaryngology and SPIRE - Sciences Po Institutional REpository.

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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