Sergio Scalise

67 total papers · 1.5k total citations
30 papers, 499 citations indexed

About

Sergio Scalise is a scholar working on Language and Linguistics, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Sergio Scalise has authored 30 papers receiving a total of 499 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Language and Linguistics, 9 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Sergio Scalise's work include Syntax, Semantics, Linguistic Variation (6 papers), Linguistic Studies and Language Acquisition (5 papers) and Spanish Linguistics and Language Studies (3 papers). Sergio Scalise is often cited by papers focused on Syntax, Semantics, Linguistic Variation (6 papers), Linguistic Studies and Language Acquisition (5 papers) and Spanish Linguistics and Language Studies (3 papers). Sergio Scalise collaborates with scholars based in Italy and Netherlands. Sergio Scalise's co-authors include Antonietta Bisetto, Rochelle Lieber, Antonio Fábregas, Elisabetta Magni, Emiliano Guevara, Irene Vogel, Antonella Ceccagno, Francesca Masini, Giorgio Graffi and Geert Booij and has published in prestigious journals such as Modern Language Journal, Language Resources and Evaluation and Lingua.

In The Last Decade

Sergio Scalise

28 papers receiving 404 citations

Author Peers

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

Author Last Decade Papers Cites
Sergio Scalise 391 177 152 118 63 30 499
Jamal Ouhalla 451 1.2× 165 0.9× 109 0.7× 138 1.2× 45 0.7× 21 520
Melita Stavrou 464 1.2× 172 1.0× 122 0.8× 146 1.2× 68 1.1× 17 494
Susana Béjar 478 1.2× 169 1.0× 122 0.8× 150 1.3× 79 1.3× 15 524
Pavol Štekauer 431 1.1× 160 0.9× 188 1.2× 132 1.1× 30 0.5× 30 573
Maria Koptjevskaja‐Tamm 382 1.0× 124 0.7× 160 1.1× 145 1.2× 32 0.5× 42 500
P. H. Matthews 367 0.9× 129 0.7× 169 1.1× 96 0.8× 47 0.7× 33 529
Robert Beard 387 1.0× 163 0.9× 119 0.8× 109 0.9× 47 0.7× 22 479
Peter Ackema 512 1.3× 237 1.3× 178 1.2× 149 1.3× 80 1.3× 32 557
M. Carme Picallo 438 1.1× 142 0.8× 141 0.9× 135 1.1× 68 1.1× 14 494
Malte Zimmermann 444 1.1× 162 0.9× 224 1.5× 155 1.3× 50 0.8× 51 527

Countries citing papers authored by Sergio Scalise

Since Specialization
Citations

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

Fields of papers citing papers by Sergio Scalise

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergio Scalise

This figure shows the co-authorship network connecting the top 25 collaborators of Sergio Scalise. A scholar is included among the top collaborators of Sergio Scalise 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 Sergio Scalise. Sergio Scalise 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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