Jamie Macbeth

25 papers receiving 572 citations

Peers

Jamie Macbeth
Comparison fields: 5 of 82
  • Computer Science Applications 72
  • Human-Computer Interaction 66
  • Communication 64
  • Social Psychology 184
  • Artificial Intelligence 195
Replace Noah Wardrip–Fruin with:
Noah Wardrip–Fruin United States
Renate Motschnig-Pitrik Austria
Daniel B. Horn United States
Mauro Cherubini Switzerland
Jofish Kaye United States
Irvin R. Katz United States
Dee H. Andrews United States
Yaxing Yao United States
Rafał Kocielnik United States
Martha E. Crosby United States
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Citations per field
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Citations per year

Countries citing papers authored by Jamie Macbeth

Since Specialization
Citations

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

Fields of papers citing papers by Jamie Macbeth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jamie Macbeth. 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 Jamie Macbeth. The network helps show where Jamie Macbeth may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016163
2 201686
3 201656
4 202035
5 201531
6 202326
7 201824
8 201024
9 201424
10
Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression.
201619
11 201618
12 201516
13
Modeling the Impact of Operator Trust on Performance in Multiple Robot Control
201315
14 201212
15 201311
16 20127
17 20194
18 20053
19
Image Schemas and Conceptual Dependency Primitives: A Comparison
20172
20 20122

About Jamie Macbeth

Jamie Macbeth is a scholar working on Social Psychology, Artificial Intelligence, Computer Networks and Communications, Sociology and Political Science and Cognitive Neuroscience, having authored 26 papers that have together received 585 indexed citations. Recurring topics across this work include Human-Automation Interaction and Safety (5 papers), Bullying, Victimization, and Aggression (4 papers), Hate Speech and Cyberbullying Detection (3 papers), Crime Patterns and Interventions (2 papers), Social Media and Politics (2 papers), Energy Efficient Wireless Sensor Networks (2 papers), Context-Aware Activity Recognition Systems (2 papers) and Language, Metaphor, and Cognition (2 papers). The work is most often cited by research in Computer Science Applications (72 citations), Human-Computer Interaction (66 citations), Communication (64 citations), Social Psychology (184 citations) and Artificial Intelligence (195 citations). Jamie Macbeth has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Desmond U. Patton, Margaret Burnett, Irwin Kwan, Stephann Makri, Anicia Peters, Simone Stumpf, Laura Beckwith, Robin M. Kowalski, Jeffrey Lane and Hongxin Hu. Their work appears in journals such as Interacting with Computers, Contemporary Justice Review, New Media & Society, IEEE Transactions on Human-Machine Systems and Journal of Human Behavior in the Social Environment.

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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