Michael Good

38 papers receiving 558 citations

Peers

Michael Good
Comparison fields: 5 of 81
  • Human-Computer Interaction 240
  • Speech and Hearing 100
  • Information Systems and Management 79
  • Cognitive Neuroscience 215
  • Signal Processing 108
Replace Candace Kamm with:
Candace Kamm United States
Martin Halvey United Kingdom
Ali Mazalek United States
Zoya Bylinskii United States
Nitin Sawhney United States
Tsuyoshi Usagawa Japan
Alejandro Catalá Spain
Lou Boves Netherlands
Raja Kushalnagar United States
George Caridakis Greece
Michael Good relative to Candace Kamm United States Candace Kamm's profile →
Citations per field
00.5×1.5×
Candace Kamm · 1×
Citations per year

Countries citing papers authored by Michael Good

Since Specialization
Citations

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

Fields of papers citing papers by Michael Good

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Michael Good, 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 Good Line = papers co-authored together Michael Good links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996130
2 1984116
3 198662
4 199529
5 201328
6 198626
7 199524
8 198223
9 200420
10 198519
11 198117
12 198116
13 199215
14 198913
15 198512
16 200212
17 198812
18 198311
19
Extensible marckup language (XML) for music applications: an introduction
200110
20 20009

About Michael Good

Michael Good is a scholar working on Human-Computer Interaction, Information Systems and Management, Speech and Hearing, Signal Processing and Cognitive Neuroscience, having authored 42 papers that have together received 667 indexed citations. Recurring topics across this work include Usability and User Interface Design (12 papers), Hearing Loss and Rehabilitation (7 papers), Personal Information Management and User Behavior (5 papers), Human-Automation Interaction and Safety (5 papers), Noise Effects and Management (4 papers), Data Visualization and Analytics (4 papers), Interactive and Immersive Displays (3 papers) and Music Technology and Sound Studies (3 papers). The work is most often cited by research in Human-Computer Interaction (240 citations), Speech and Hearing (100 citations), Information Systems and Management (79 citations), Cognitive Neuroscience (215 citations) and Signal Processing (108 citations). Michael Good has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Robert H. Gilkey, John Whiteside, Dennis Wixon, Sandra J. Jones, Patrick George, Norm Archer, Michael C. Dorneich, Mark A. Ericson, John Stewart and Patricia May Ververs. Their work appears in journals such as The Journal of the Acoustical Society of America, ACM SIGPLAN Notices, SAE technical papers on CD-ROM/SAE technical paper series, Human Factors The Journal of the Human Factors and Ergonomics Society and Communications of the ACM.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026