David Vilares

111 total papers · 1.6k total citations
40 papers, 709 citations indexed

About

David Vilares is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, David Vilares has authored 40 papers receiving a total of 709 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 6 papers in Information Systems and 5 papers in Sociology and Political Science. Recurrent topics in David Vilares's work include Topic Modeling (27 papers), Sentiment Analysis and Opinion Mining (22 papers) and Natural Language Processing Techniques (16 papers). David Vilares is often cited by papers focused on Topic Modeling (27 papers), Sentiment Analysis and Opinion Mining (22 papers) and Natural Language Processing Techniques (16 papers). David Vilares collaborates with scholars based in Spain, China and Singapore. David Vilares's co-authors include Carlos Gómez‐Rodríguez, Miguel Á. Alonso, Jesús Vilares, Erik Cambria, Mike Thelwall, Haiyun Peng, Ranjan Satapathy, Yulan He, Iti Chaturvedi and A.G. López‐Herrera and has published in prestigious journals such as Knowledge-Based Systems, Information Processing & Management and Artificial Intelligence Review.

In The Last Decade

David Vilares

40 papers receiving 672 citations

Hit Papers

Sentiment Analysis for Fa... 2021 2026 2022 2024 2021 40 80 120

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David Vilares 575 192 154 44 44 40 709
Miguel Á. Alonso 583 1.0× 288 1.5× 192 1.2× 36 0.8× 40 0.9× 76 839
Matheus Araújo 355 0.6× 210 1.1× 101 0.7× 47 1.1× 61 1.4× 26 629
Marco Lui 693 1.2× 76 0.4× 115 0.7× 45 1.0× 50 1.1× 17 819
Ivan Habernal 633 1.1× 84 0.4× 178 1.2× 23 0.5× 31 0.7× 38 694
Farah Benamara 560 1.0× 74 0.4× 103 0.7× 26 0.6× 37 0.8× 46 664
Roy Ka-Wei Lee 522 0.9× 104 0.5× 115 0.7× 63 1.4× 46 1.0× 60 699
Thai Le 320 0.6× 340 1.8× 141 0.9× 23 0.5× 119 2.7× 28 667
Nina Wacholder 722 1.3× 72 0.4× 244 1.6× 37 0.8× 42 1.0× 40 895
Serena Villata 639 1.1× 130 0.7× 166 1.1× 21 0.5× 42 1.0× 74 783
Shaodian Zhang 665 1.2× 73 0.4× 122 0.8× 40 0.9× 42 1.0× 26 905

Countries citing papers authored by David Vilares

Since Specialization
Citations

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

Fields of papers citing papers by David Vilares

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Vilares

This figure shows the co-authorship network connecting the top 25 collaborators of David Vilares. A scholar is included among the top collaborators of David Vilares 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 David Vilares. David Vilares is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Loading papers...

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026