David Massimo

560 citations
20 papers · 328 · h-index 10

Impact in

Papers in

David Massimo

19 papers receiving 316 citations

Peers

David Massimo
Comparison fields: 5 of 62
  • Information Systems 210
  • Transportation 32
  • Computer Vision and Pattern Recognition 76
  • Human-Computer Interaction 20
  • Computer Science Applications 16
Replace Martin Stettinger with:
Martin Stettinger Austria
Noemi Mauro Italy
Gawesh Jawaheer United Kingdom
Leonardo A. Martucci Sweden
Tuul Triyason Thailand
Rickard Cöster Sweden
Davar Pishva Japan
Müslüm Atas Austria
Jawad Berri Saudi Arabia
Nitin Gupta India
David Massimo relative to Martin Stettinger Austria Martin Stettinger's profile →
Citations per field
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Citations per year

Countries citing papers authored by David Massimo

Since Specialization
Citations

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

Fields of papers citing papers by David Massimo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside David Massimo, 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 David Massimo Line = papers co-authored together David Massimo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201596
2 201584
3 201830
4 202117
5
Interaction Design in a Mobile Food Recommender System
201514
6 202314
7 202214
8 202312
9 201711
10
Interactive Food Recommendation for Groups
201410
11 20178
12 20186
13 20203
14 20182
15 20212
16 20232
17 20151
18 20231
19 20241
20 20230

About David Massimo

David Massimo is a scholar working on Information Systems, Sociology and Political Science, Marketing, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 20 papers that have together received 328 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (13 papers), Digital Marketing and Social Media (5 papers), Advanced Bandit Algorithms Research (4 papers), Innovative Human-Technology Interaction (4 papers), Consumer Market Behavior and Pricing (3 papers), Sharing Economy and Platforms (2 papers), Transportation and Mobility Innovations (2 papers) and Artificial Intelligence in Games (2 papers). The work is most often cited by research in Information Systems (210 citations), Transportation (32 citations), Computer Vision and Pattern Recognition (76 citations), Human-Computer Interaction (20 citations) and Computer Science Applications (16 citations). David Massimo has collaborated with scholars based in Italy, Spain and Australia. Frequent co-authors include Francesco Ricci⋆, Mouzhi Ge, Mehdi Elahi, Katerina Berezina, Berta Ferrer-Rosell, Shlomo Berkovsky, Ignacio Fernández-Tobías, Elena Not, Antonella De Angeli and Attaullah Buriro. Their work appears in journals such as Information Technology & Tourism, AI Magazine, IEEE Transactions on Instrumentation and Measurement, View and Scopus (Elsevier).

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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