Daniel Avrahami

3.1k citations
42 papers · 2.3k · h-index 23

Impact in

Papers in

Daniel Avrahami

42 papers receiving 2.1k citations

Peers

Daniel Avrahami
Comparison fields: 5 of 108
  • Human-Computer Interaction 1.1k
  • Information Systems and Management 621
  • Applied Psychology 272
  • Computer Vision and Pattern Recognition 552
  • Health Informatics 34
Replace Jo Vermeulen with:
Jo Vermeulen Denmark
Simo Hosio Finland
Effie Lai‐Chong Law United Kingdom
Joel E. Fischer United Kingdom
Niels van Berkel Denmark
Heinrich Hußmann Germany
Mark Newman United States
Tilman Dingler Australia
Khai N. Truong Canada
Eun Kyoung Choe United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Avrahami

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Avrahami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Avrahami, 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 Daniel Avrahami Line = papers co-authored together Daniel Avrahami 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 2009344
2 2008309
3 2005236
4 2003223
5 2018138
6 200984
7 200480
8 201878
9 200665
10 200257
11 201647
12 201146
13 201744
14 200643
15 200841
16 201941
17 200638
18 201636
19 201031
20 200431

About Daniel Avrahami

Daniel Avrahami is a scholar working on Human-Computer Interaction, Information Systems and Management, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Social Psychology, having authored 42 papers that have together received 2.3k indexed citations. Recurring topics across this work include Personal Information Management and User Behavior (19 papers), Interactive and Immersive Displays (12 papers), Usability and User Interface Design (9 papers), Tactile and Sensory Interactions (7 papers), Context-Aware Activity Recognition Systems (6 papers), Innovative Human-Technology Interaction (6 papers), Team Dynamics and Performance (5 papers) and Augmented Reality Applications (5 papers). The work is most often cited by research in Human-Computer Interaction (1.1k citations), Information Systems and Management (621 citations), Applied Psychology (272 citations), Computer Vision and Pattern Recognition (552 citations) and Health Informatics (34 citations). Daniel Avrahami has collaborated with scholars based in United States, Japan and Netherlands. Frequent co-authors include Scott E. Hudson, Brian Y. Lim, Anind K. Dey, Jodi Forlizzi, James Fogarty, Sara Kiesler, Christopher G. Atkeson, Rafał Kocielnik, Gary Hsieh and Johnny C. Lee. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Information Polity, Behaviour and Information Technology, ACM Transactions on Computer-Human Interaction and ACM Transactions on Interactive Intelligent Systems.

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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