Nina Valkanova
- Human-Computer Interaction top 1%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Sociology and Political Science
- Computer Science Applications top 10%
- Co-authors
- Andrew Vande MoereRobert WalterJörg MüllerSergi JordàMartin TomitschGilles BaillyAva Fatah gen. SchieckDuncan P. Brumby
- Topics
- Innovative Human-Technology Interaction (8 papers)Interactive and Immersive Displays (7 papers)Data Visualization and Analytics (3 papers)
- Cited by
- Human-Computer InteractionComputer Science ApplicationsComputer Vision and Pattern Recognition
- Journals
- International Journal of Human-Computer StudiesIEEE Computer Graphics and Applicationsi-com
- Partner nations
- SpainUnited KingdomBelgium
In The Last Decade
Nina Valkanova
16 papers receiving 397 citations
Peers
Comparison fields: 5 of 55
- Human-Computer Interaction 317
- Computer Vision and Pattern Recognition 104
- Cognitive Neuroscience 95
- Sociology and Political Science 57
- Computer Science Applications 44
Countries citing papers authored by Nina Valkanova
This map shows the geographic impact of Nina Valkanova'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 Nina Valkanova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina Valkanova more than expected).
Fields of papers citing papers by Nina Valkanova
This network shows the impact of papers produced by Nina Valkanova. 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 Nina Valkanova. The network helps show where Nina Valkanova may publish in the future.
Co-authorship network of co-authors of Nina Valkanova
This figure shows the co-authorship network connecting the top 25 collaborators of Nina Valkanova. A scholar is included among the top collaborators of Nina Valkanova based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nina Valkanova. Nina Valkanova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 3 | |
| 3 | Prototyping Feedback for Technology Enhanced Learning | 4 |
| 4 | Opening the black box of practice-based learning: Human-centred design of learning analytics | 1 |
| 5 | Information-Bombing: Confronting the Public to Civic Data | 1 |
| 6 | 28 | |
| 7 | 64 | |
| 8 | 87 | |
| 9 | 2 | |
| 10 | 47 | |
| 11 | 20 | |
| 12 | 24 | |
| 13 | 76 | |
| 14 | 15 | |
| 15 | 5 | |
| 16 | 6 |
About Nina Valkanova
Nina Valkanova is a scholar working on Human-Computer Interaction, Architecture and Computer Science Applications, having authored 16 papers that have together received 403 indexed citations. Recurring topics across this work include Innovative Human-Technology Interaction (8 papers), Interactive and Immersive Displays (7 papers) and Data Visualization and Analytics (3 papers). The work is most often cited by research in Human-Computer Interaction (317 citations), Computer Science Applications (44 citations) and Computer Vision and Pattern Recognition (104 citations). Nina Valkanova has collaborated with scholars based in Spain, United Kingdom and Belgium. Frequent co-authors include Andrew Vande Moere, Robert Walter, Jörg Müller, Sergi Jordà, Martin Tomitsch, Gilles Bailly, Ava Fatah gen. Schieck, Duncan P. Brumby, Sheelagh Carpendale and Uta Hinrichs. Their work appears in journals such as International Journal of Human-Computer Studies, IEEE Computer Graphics and Applications and i-com.
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.