Hanna Schäfer

687 total citations
26 papers, 444 citations indexed

About

Hanna Schäfer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and General Health Professions. According to data from OpenAlex, Hanna Schäfer has authored 26 papers receiving a total of 444 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 7 papers in General Health Professions. Recurrent topics in Hanna Schäfer's work include Mobile Health and mHealth Applications (7 papers), Recommender Systems and Techniques (6 papers) and Educational Games and Gamification (5 papers). Hanna Schäfer is often cited by papers focused on Mobile Health and mHealth Applications (7 papers), Recommender Systems and Techniques (6 papers) and Educational Games and Gamification (5 papers). Hanna Schäfer collaborates with scholars based in Germany, Sweden and Portugal. Hanna Schäfer's co-authors include Mennatallah El‐Assady, Udo Schlegel, Alan Said, Georg Groh, Helma Torkamaan, Christoph Trattner, Tom Florian Ulmer, Martijn C. Willemsen, André Calero Valdez and Christina Holzapfel and has published in prestigious journals such as Nutrients, Journal of the Association for Information Systems and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Hanna Schäfer

26 papers receiving 431 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hanna Schäfer Germany 9 178 113 101 83 57 26 444
Robin De Croon Belgium 11 64 0.4× 55 0.5× 72 0.7× 61 0.7× 25 0.4× 31 354
Rieks op den Akker Netherlands 16 381 2.1× 68 0.6× 41 0.4× 101 1.2× 17 0.3× 62 696
Anmol Madan United States 10 111 0.6× 90 0.8× 68 0.7× 33 0.4× 20 0.4× 16 673
Andrew Macvean United States 12 97 0.5× 33 0.3× 136 1.3× 39 0.5× 20 0.4× 32 475
Patrick Lange United States 9 260 1.5× 67 0.6× 19 0.2× 70 0.8× 19 0.3× 38 444
Maurizio Tucci Italy 15 164 0.9× 154 1.4× 73 0.7× 21 0.3× 11 0.2× 54 560
Emma Anderson United Kingdom 7 58 0.3× 116 1.0× 68 0.7× 32 0.4× 13 0.2× 18 389
Hafiz Syed Muhammad Bilal South Korea 11 135 0.8× 56 0.5× 66 0.7× 18 0.2× 40 0.7× 32 467
Randi Karlsen Norway 9 118 0.7× 32 0.3× 96 1.0× 101 1.2× 19 0.3× 47 473
Maria Beatriz Carmo Portugal 10 50 0.3× 118 1.0× 30 0.3× 40 0.5× 8 0.1× 74 355

Countries citing papers authored by Hanna Schäfer

Since Specialization
Citations

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

Fields of papers citing papers by Hanna Schäfer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanna Schäfer

This figure shows the co-authorship network connecting the top 25 collaborators of Hanna Schäfer. A scholar is included among the top collaborators of Hanna Schäfer 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 Hanna Schäfer. Hanna Schäfer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schäfer, Hanna, et al.. (2021). Explaining Contextualization in Language Models using Visual Analytics. Data Archiving and Networked Services (DANS). 464–476. 8 indexed citations
2.
Sperrle, Fabian, Hanna Schäfer, Daniel A. Keim, & Mennatallah El‐Assady. (2021). Learning Contextualized User Preferences for Co‐Adaptive Guidance in Mixed‐Initiative Topic Model Refinement. Computer Graphics Forum. 40(3). 215–226. 13 indexed citations
3.
Schäfer, Hanna, David A. Plecher, Lynne Stecher, et al.. (2020). Serious Games for Nutritional Education: Online Survey on Preferences, Motives, and Behaviors Among Young Adults at University. JMIR Serious Games. 8(2). e16216–e16216. 3 indexed citations
4.
Kraus, Matthias, Hanna Schäfer, Daniel Schweitzer, et al.. (2020). A Comparative Study of Orientation Support Tools in Virtual Reality Environments with Virtual Teleportation. KOPS (University of Konstanz). 227–238. 5 indexed citations
5.
Said, Alan, Hanna Schäfer, Helma Torkamaan, & Christoph Trattner. (2020). Fifth International Workshop on Health Recommender Systems (HealthRecSys 2020). Data Archiving and Networked Services (DANS). 611–612. 3 indexed citations
6.
Schäfer, Hanna, et al.. (2019). Shall we play? – Extending the Visual Analytics Design Space through Gameful Design Concepts. 105. 1–9. 2 indexed citations
7.
Schäfer, Hanna, Georg Groh, David A. Plecher, et al.. (2019). Short-Term Effects of the Serious Game “Fit, Food, Fun” on Nutritional Knowledge: A Pilot Study among Children and Adolescents. Nutrients. 11(9). 2031–2031. 28 indexed citations
8.
Schäfer, Hanna, et al.. (2019). Digital Gaming for Nutritional Education: A Survey on Preferences, Motives, and Needs of Children and Adolescents. JMIR Formative Research. 3(1). e10284–e10284. 19 indexed citations
9.
Schäfer, Hanna & Martijn C. Willemsen. (2019). Rasch-based tailored goals for nutrition assistance systems. TU/e Research Portal. 18–29. 23 indexed citations
10.
Schäfer, Hanna, et al.. (2019). Framing Visual Musicology through Methodology Transfer. 2 indexed citations
11.
Schlegel, Udo, et al.. (2019). explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning. IEEE Transactions on Visualization and Computer Graphics. 26(1). 1–1. 150 indexed citations
12.
Schäfer, Hanna, et al.. (2018). Nutrilize a Personalized Nutrition Recommender System: an Enable Study.. mediaTUM (Technical University of Munich). 24–29. 16 indexed citations
13.
Elsweiler, David, Bernd Ludwig, Alan Said, et al.. (2018). Third international workshop on health recommender systems (healthrecsys 2018). 517–518. 3 indexed citations
14.
Schäfer, Hanna, Mehdi Elahi, David Elsweiler, et al.. (2017). User Nutrition Modelling and Recommendation. View. 93–96. 11 indexed citations
15.
Elsweiler, David, Bernd Ludwig, Alan Said, et al.. (2017). Second Workshop on Health Recommender Systems. Research Publications (Maastricht University). 374–375. 7 indexed citations
16.
Schäfer, Hanna, et al.. (2016). Can an Automated Personalized Nutrition Assistance System Successfully Change Nutrition Behavior? - Study Design. Journal of the Association for Information Systems. 7 indexed citations
17.
Schäfer, Hanna. (2016). Personalized Support for Healthy Nutrition Decisions. 455–458. 5 indexed citations
18.
Schäfer, Hanna, et al.. (2015). Personalized Food Recommendation.. 21–24. 3 indexed citations
19.
Viegas, Joaquim L., et al.. (2015). Fuzzy modeling based on Mixed Fuzzy Clustering for health care applications. 18. 1–5. 6 indexed citations
20.
Schäfer, Hanna, et al.. (2015). Analysing the segmentation of energy consumers using mixed fuzzy clustering. 8. 1–7. 6 indexed citations

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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