Felipe Viegas

845 citations
27 papers · 543 indexed · h-index 11
Topics
Text and Document Classification Technologies (15 papers)Topic Modeling (13 papers)Advanced Text Analysis Techniques (10 papers)
Journals
SHILAP Revista de lepidopterologíaACM Computing SurveysInformation Sciences

In The Last Decade

Felipe Viegas

24 papers receiving 529 citations

Peers

Felipe Viegas
Comparison fields: 5 of 118
  • Artificial Intelligence 321
  • Information Systems 111
  • Molecular Biology 60
  • Pharmaceutical Science 46
  • General Social Sciences 35
Replace Shivam Agarwal with:
Shivam Agarwal India
Meena Nagarajan India
Rajesh Prasad India
Hai Wang United Kingdom
Arushi Jain India
Yilei Wang China
Irene Li United States
Jiajun Cheng China
Howard Ho United States
Felipe Viegas relative to Shivam Agarwal India Shivam Agarwal's profile →
Citations per field
00.5×5.8×
Shivam Agarwal · 1×
Citations per year

Countries citing papers authored by Felipe Viegas

Since Specialization
Citations

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

Fields of papers citing papers by Felipe Viegas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Felipe Viegas

This figure shows the co-authorship network connecting the top 25 collaborators of Felipe Viegas. A scholar is included among the top collaborators of Felipe Viegas 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 Felipe Viegas. Felipe Viegas 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 0
2 1
3 0
4 18
5 2
6 24
7 1
8 4
9 8
10 8
11 126
12 56
13 21
14 21
15 1
16 66
17 7
18 5
19 5
20 16

About Felipe Viegas

Felipe Viegas is a scholar working on General Social Sciences, Artificial Intelligence and Information Systems, having authored 27 papers that have together received 543 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (15 papers), Topic Modeling (13 papers) and Advanced Text Analysis Techniques (10 papers). The work is most often cited by research in General Social Sciences (35 citations), Artificial Intelligence (321 citations) and Pharmaceutical Science (46 citations). Felipe Viegas has collaborated with scholars based in Brazil, Portugal and United States. Frequent co-authors include Leonardo Rocha, Marcos André Gonçalves, Thiago Salles, Thierson Couto Rosa, Sérgio Canuto, Fernando Mourão, Christian Gomes, Marlus Chorilli, Delia Rita Tapia‐Blácido and Juliana Palma Abriata. Their work appears in journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Information Sciences.

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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