Flávia Bernardini

77 papers receiving 462 citations

Peers

Flávia Bernardini
Comparison fields: 5 of 98
  • Computer Science Applications 43
  • Media Technology 51
  • Human-Computer Interaction 27
  • Artificial Intelligence 135
  • Information Systems 94
Replace José Viterbo with:
José Viterbo Brazil
Neil Y. Yen Japan
Joaquín Salvachúa Spain
Andreas Menychtas Greece
Asmaa Munshi Saudi Arabia
Silvana Aciar Argentina
Shahreen Kasim Malaysia
Supeno Mardi Susiki Nugroho Indonesia
Anastasios Zafeiropoulos Greece
Md Ileas Pramanik Bangladesh
Flávia Bernardini relative to José Viterbo Brazil José Viterbo's profile →
Citations per field
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José Viterbo · 1×
Citations per year

Countries citing papers authored by Flávia Bernardini

Since Specialization
Citations

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

Fields of papers citing papers by Flávia Bernardini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Flávia Bernardini, 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 Flávia Bernardini Line = papers co-authored together Flávia Bernardini links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202253
2 202125
3 202124
4 201922
5 200822
6 201922
7 202122
8 201716
9 202015
10 201814
11 201813
12 201813
13 202111
14 202111
15 20209
16 20238
17 20218
18 20248
19 20148
20 20208

About Flávia Bernardini

Flávia Bernardini is a scholar working on Artificial Intelligence, Political Science and International Relations, Media Technology, Information Systems and Computer Vision and Pattern Recognition, having authored 90 papers that have together received 491 indexed citations. Recurring topics across this work include E-Government and Public Services (22 papers), Smart Cities and Technologies (19 papers), Big Data and Business Intelligence (10 papers), Data Quality and Management (8 papers), Data Stream Mining Techniques (8 papers), IoT and Edge/Fog Computing (6 papers), Innovative Approaches in Technology and Social Development (6 papers) and Education and Digital Technologies (5 papers). The work is most often cited by research in Computer Science Applications (43 citations), Media Technology (51 citations), Human-Computer Interaction (27 citations), Artificial Intelligence (135 citations) and Information Systems (94 citations). Flávia Bernardini has collaborated with scholars based in Brazil, Netherlands and Portugal. Frequent co-authors include José Viterbo, Leandro Miranda, Daniela Trevisan, Ana Cristina Bicharra García, Cláudia Cappelli, Victor Chang, Simone Bacellar Leal Ferreira, Paulo F. Pires, Leonardo dos Santos and Aline Paes. Their work appears in journals such as Journal of the Association for Information Systems, Telematics and Informatics, Computers & Graphics, Information Sciences and Artificial Intelligence Review.

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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