Ana Azevedo

769 citations
37 papers · 416 indexed · h-index 9
Topics
Big Data and Business Intelligence (8 papers)Data Mining Algorithms and Applications (5 papers)Technology Adoption and User Behaviour (4 papers)

In The Last Decade

Ana Azevedo

33 papers receiving 372 citations

Peers

Ana Azevedo
Comparison fields: 5 of 100
  • Sociology and Political Science 90
  • Information Systems 84
  • Management Information Systems 73
  • Artificial Intelligence 68
  • Communication 53
Replace Helena Alvelos with:
Helena Alvelos Portugal
Stefan Cronholm Sweden
Elaine Ferneley United Kingdom
Hulya Julie Yazici United States
Gianluigi Viscusi Italy
Marija Čubrić United Kingdom
Luke Houghton Australia
Bernard T. Han United States
Urban Nuldén Sweden
Jan Nolin Sweden
Ana Azevedo relative to Helena Alvelos Portugal Helena Alvelos's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ana Azevedo

Since Specialization
Citations

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

Fields of papers citing papers by Ana Azevedo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ana Azevedo

This figure shows the co-authorship network connecting the top 25 collaborators of Ana Azevedo. A scholar is included among the top collaborators of Ana Azevedo 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 Ana Azevedo. Ana Azevedo 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
#WorkIndexed citations
1 3
2 3
3 0
4 4
5 9
6 1
7 0
8 4
9 1
10 1
11 1
12 5
13 5
14
Planning and implementing a new assessment strategy using an e-learning platform
3
15
Binding data mining to final business users of business intelligence systems
1
16 0
17 12
18
An architecture for an effective usage of data mining in business intelligence systems
1
19
KDD, SEMMA AND CRISP-DM: A PARALLEL OVERVIEW
153
20
Developing an information system at the Engineering Faculty of Porto University
2

About Ana Azevedo

Ana Azevedo is a scholar working on Management Information Systems, Computer Science Applications and Information Systems and Management, having authored 37 papers that have together received 416 indexed citations. Recurring topics across this work include Big Data and Business Intelligence (8 papers), Data Mining Algorithms and Applications (5 papers) and Technology Adoption and User Behaviour (4 papers). The work is most often cited by research in Computer Science Applications (46 citations), Management Information Systems (73 citations) and Communication (53 citations). Ana Azevedo has collaborated with scholars based in Portugal, Brazil and United States. Frequent co-authors include Manuel Filipe Santos, Daniel Robey, Michael R. Mullen, Ellen A. Drost, Artur Strzelecki, Jarkko Suhonen, Mariia Rizun, Paulina Rutecka, Karen Paul and Deolinda Meira. Their work appears in journals such as International Journal of Environmental Research and Public Health, Sustainability and Healthcare.

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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