Eva Mayr
Impact in
- Human-Computer Interaction top 5%
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- Data Visualization and Analytics
- Video Analysis and Summarization
Papers in
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- Data Visualization and Analytics 33
- Video Analysis and Summarization 10
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- Digital Humanities and Scholarship 11
- Co-authors
- Florian Windhager (37 shared papers)Michael Smuc (24 shared papers)Günther Schreder (18 shared papers)Silvia Miksch (10 shared papers)Paolo Federico (3 shared papers)Ulrike Willinger (1 shared paper)Marian Dörk (2 shared papers)Ulrike Sirsch (1 shared paper)
In The Last Decade
Eva Mayr
61 papers receiving 645 citations
Peers
Comparison fields: 5 of 101
- Human-Computer Interaction 98
- Computer Vision and Pattern Recognition 354
- Museology 48
- Neuropsychology and Physiological Psychology 18
- Ecological Modeling 27
Countries citing papers authored by Eva Mayr
This map shows the geographic impact of Eva Mayr'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 Eva Mayr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Mayr more than expected).
Fields of papers citing papers by Eva Mayr
This network shows the impact of papers produced by Eva Mayr. 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 Eva Mayr. The network helps show where Eva Mayr may publish in the future.
Co-authors
The 25 scholars most cited alongside Eva Mayr, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 136 | |
| 2 | 2009 | 81 | |
| 3 | 2009 | 33 | |
| 4 | 2012 | 32 | |
| 5 | 2009 | 29 | |
| 6 | 2011 | 28 | |
| 7 | 2009 | 28 | |
| 8 | 2013 | 24 | |
| 9 | 2018 | 23 | |
| 10 | 2019 | 23 | |
| 11 | 2019 | 22 | |
| 12 | In-sights into mobile learning: An exploration of mobile eye tracking methodology for learning in museums | 2009 | 21 |
| 13 | 2021 | 17 | |
| 14 | 2008 | 16 | |
| 15 | 2013 | 15 | |
| 16 | 2016 | 12 | |
| 17 | 2016 | 11 | |
| 18 | Potentials and Challenges of Mobile Media in Museums | 2007 | 10 |
| 19 | 2009 | 9 | |
| 20 | 2020 | 9 |
About Eva Mayr
Eva Mayr is a scholar working on Computer Vision and Pattern Recognition, Literature and Literary Theory, Artificial Intelligence, Sociology and Political Science and Experimental and Cognitive Psychology, having authored 69 papers that have together received 696 indexed citations. Recurring topics across this work include Data Visualization and Analytics (33 papers), Digital Humanities and Scholarship (11 papers), Video Analysis and Summarization (10 papers), Visual and Cognitive Learning Processes (8 papers), Museums and Cultural Heritage (8 papers), Multimedia Communication and Technology (7 papers), Advanced Text Analysis Techniques (7 papers) and Semantic Web and Ontologies (5 papers). The work is most often cited by research in Human-Computer Interaction (98 citations), Computer Vision and Pattern Recognition (354 citations), Museology (48 citations), Neuropsychology and Physiological Psychology (18 citations) and Ecological Modeling (27 citations). Eva Mayr has collaborated with scholars based in Austria, Germany and Denmark. Frequent co-authors include Florian Windhager, Michael Smuc, Günther Schreder, Silvia Miksch, Paolo Federico, Ulrike Willinger, Marian Dörk, Ulrike Sirsch, Hanna Risku and Margit Pohl. Their work appears in journals such as IEEE Computer Graphics and Applications, Informatics, IEEE Transactions on Visualization and Computer Graphics, Frontiers in Oncology and Information Visualization.
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.