Andrea Esuli

168 total papers · 9.0k total citations
79 papers, 5.2k citations indexed

About

Andrea Esuli is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Andrea Esuli has authored 79 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 17 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Andrea Esuli's work include Topic Modeling (28 papers), Text and Document Classification Technologies (24 papers) and Sentiment Analysis and Opinion Mining (20 papers). Andrea Esuli is often cited by papers focused on Topic Modeling (28 papers), Text and Document Classification Technologies (24 papers) and Sentiment Analysis and Opinion Mining (20 papers). Andrea Esuli collaborates with scholars based in Italy, United States and Qatar. Andrea Esuli's co-authors include Fabrizio Sebastiani, Stefano Baccianella, Alejandro Moreo, Alessio Ferrari, Fabrizio Falchi, Giuseppe Amato, Nicola Messina, Diego Marcheggiani, Tiziano Fagni and Stéphane Marchand‐Maillet and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Andrea Esuli

74 papers receiving 4.7k citations

Hit Papers

SentiWordNet 3.0: An Enha... 2006 2026 2012 2019 2010 2006 500 1000 1.5k

Author Peers

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

Author Last Decade Papers Cites
Andrea Esuli 4.4k 1.2k 555 402 311 79 5.2k
Bo Pang 5.2k 1.2× 1.5k 1.3× 683 1.2× 485 1.2× 387 1.2× 56 6.2k
Hanna Wallach 3.0k 0.7× 744 0.6× 575 1.0× 405 1.0× 349 1.1× 67 4.9k
Ahmed H. Yousef 2.4k 0.6× 1.5k 1.3× 538 1.0× 218 0.5× 230 0.7× 115 4.0k
Steven Bird 4.9k 1.1× 1.2k 1.1× 553 1.0× 689 1.7× 200 0.6× 134 6.8k
Jordan Boyd‐Graber 3.5k 0.8× 636 0.5× 506 0.9× 548 1.4× 294 0.9× 124 4.9k
Alan Ritter 4.4k 1.0× 879 0.7× 321 0.6× 616 1.5× 465 1.5× 71 5.2k
Jacob Eisenstein 3.9k 0.9× 949 0.8× 635 1.1× 570 1.4× 398 1.3× 113 5.5k
Ellen Riloff 5.5k 1.3× 1.3k 1.1× 226 0.4× 268 0.7× 175 0.6× 102 6.2k
Xiaodan Zhu 3.9k 0.9× 530 0.5× 521 0.9× 676 1.7× 248 0.8× 180 5.4k
Catherine Havasi 3.4k 0.8× 582 0.5× 366 0.7× 648 1.6× 163 0.5× 39 4.1k

Countries citing papers authored by Andrea Esuli

Since Specialization
Citations

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

Fields of papers citing papers by Andrea Esuli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Esuli

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