Fernando Díez

86 total papers · 851 total citations
33 papers, 459 citations indexed

About

Fernando Díez is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Fernando Díez has authored 33 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Information Systems, 5 papers in Artificial Intelligence and 3 papers in Computer Networks and Communications. Recurrent topics in Fernando Díez's work include Recommender Systems and Techniques (8 papers), Latin American Urban Studies (3 papers) and Misinformation and Its Impacts (3 papers). Fernando Díez is often cited by papers focused on Recommender Systems and Techniques (8 papers), Latin American Urban Studies (3 papers) and Misinformation and Its Impacts (3 papers). Fernando Díez collaborates with scholars based in Spain, Chile and Argentina. Fernando Díez's co-authors include Pedro G. Campos, Iván Cantador, Alejandro Bellogín, Pablo Castells, Ruth Cobos, Manuel Sánchez-Montañés, Roberto Moriyón, Francisco Jurado, M. Giménez and Pilar Rodrı́guez and has published in prestigious journals such as Information Processing & Management, User Modeling and User-Adapted Interaction and ACM Transactions on Intelligent Systems and Technology.

In The Last Decade

Fernando Díez

31 papers receiving 429 citations

Hit Papers

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Author Peers

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

Author Last Decade Papers Cites
Fernando Díez 346 154 96 89 63 33 459
Simon Dooms 355 1.0× 156 1.0× 125 1.3× 63 0.7× 72 1.1× 25 424
María Salamó 320 0.9× 258 1.7× 74 0.8× 106 1.2× 36 0.6× 49 549
Fernando Mourão 256 0.7× 273 1.8× 61 0.6× 46 0.5× 75 1.2× 48 506
Mohammad Yahya H. Al-Shamri 371 1.1× 185 1.2× 134 1.4× 72 0.8× 94 1.5× 20 512
Ana Peleteiro 280 0.8× 99 0.6× 109 1.1× 62 0.7× 64 1.0× 18 422
Xin Liu 306 0.9× 238 1.5× 119 1.2× 37 0.4× 86 1.4× 44 513
Matevž Kunaver 297 0.9× 153 1.0× 77 0.8× 73 0.8× 40 0.6× 17 447
Maryam Khanian Najafabadi 296 0.9× 161 1.0× 63 0.7× 49 0.6× 72 1.1× 22 500
Bharat Bhasker 238 0.7× 189 1.2× 56 0.6× 52 0.6× 68 1.1× 40 458
Amin Mantrach 238 0.7× 285 1.9× 98 1.0× 65 0.7× 41 0.7× 19 545

Countries citing papers authored by Fernando Díez

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Díez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Díez

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

All Works

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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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