Francesco Barbieri

95 total papers · 2.5k total citations
42 papers, 1.1k citations indexed

About

Francesco Barbieri is a scholar working on Artificial Intelligence, Human-Computer Interaction and Experimental and Cognitive Psychology. According to data from OpenAlex, Francesco Barbieri has authored 42 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 8 papers in Human-Computer Interaction and 6 papers in Experimental and Cognitive Psychology. Recurrent topics in Francesco Barbieri's work include Sentiment Analysis and Opinion Mining (21 papers), Topic Modeling (14 papers) and Natural Language Processing Techniques (10 papers). Francesco Barbieri is often cited by papers focused on Sentiment Analysis and Opinion Mining (21 papers), Topic Modeling (14 papers) and Natural Language Processing Techniques (10 papers). Francesco Barbieri collaborates with scholars based in Spain, United States and United Kingdom. Francesco Barbieri's co-authors include Horacio Saggion, Francesco Ronzano, Luis Espinosa-Anke, Miguel Ballesteros, José Camacho-Collados, Germán Kruszewski, Xavier Serra, Oriol Nieto, Sergio Oramas and Leonardo Neves and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Affective Computing and Language Resources and Evaluation.

In The Last Decade

Francesco Barbieri

40 papers receiving 984 citations

Author Peers

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

Author Last Decade Papers Cites
Francesco Barbieri 759 259 131 120 107 42 1.1k
Anbang Xu 541 0.7× 130 0.5× 184 1.4× 124 1.0× 49 0.5× 45 1.2k
Candace Kamm 819 1.1× 183 0.7× 58 0.4× 195 1.6× 123 1.1× 37 1.4k
Oya Aran 387 0.5× 287 1.1× 308 2.4× 305 2.5× 78 0.7× 63 1.1k
Hugo Liu 647 0.9× 91 0.4× 96 0.7× 146 1.2× 55 0.5× 23 1.1k
Ching‐Hua Chuan 296 0.4× 204 0.8× 194 1.5× 93 0.8× 143 1.3× 41 1.0k
Mariët Theune 967 1.3× 75 0.3× 162 1.2× 203 1.7× 55 0.5× 123 1.3k
Charles Callaway 527 0.7× 159 0.6× 155 1.2× 191 1.6× 23 0.2× 44 989
Cecilia Ovesdotter Alm 702 0.9× 71 0.3× 183 1.4× 217 1.8× 51 0.5× 89 1.2k
David Griol 701 0.9× 107 0.4× 118 0.9× 185 1.5× 83 0.8× 96 1.1k
Zoraida Callejas 736 1.0× 128 0.5× 140 1.1× 234 1.9× 97 0.9× 97 1.2k

Countries citing papers authored by Francesco Barbieri

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Barbieri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Barbieri

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