Marc Franco-Salvador

23 papers receiving 332 citations

Peers

Marc Franco-Salvador
Comparison fields: 5 of 48
  • Artificial Intelligence 314
  • Information Systems 60
  • Safety Research 53
  • Social Psychology 15
  • Computer Vision and Pattern Recognition 15
Replace Esaú Villatoro-Tello with:
Esaú Villatoro-Tello Mexico
Ashwin Kalyan United States
Leilani H. Gilpin United States
Md Mehrab Tanjim United States
Ángel Alexander Cabrera United States
Joe Barrow United States
Nouha Dziri United States
Shrimai Prabhumoye United States
Rashidul Islam United States
Michael Schlichtkrull United Kingdom
Marc Franco-Salvador relative to Esaú Villatoro-Tello Mexico Esaú Villatoro-Tello's profile →
Citations per field
00.5×1.5×2.0×
Esaú Villatoro-Tello · 1×
Citations per year

Countries citing papers authored by Marc Franco-Salvador

Since Specialization
Citations

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

Fields of papers citing papers by Marc Franco-Salvador

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc Franco-Salvador. 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 Marc Franco-Salvador. The network helps show where Marc Franco-Salvador may publish in the future.

Co-authorship network of co-authors of Marc Franco-Salvador

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 16
4
UPV-Symanto at eRisk 2021: Mental Health Author Profiling for Early Risk Prediction on the Internet.
3
5 11
6 1
7 3
8 1
9 15
10
CATS: A Tool for Customized Alignment of Text Simplification Corpora
26
11 12
12
Subword-based Deep Averaging Networks for Author Profiling in Social Media.
8
13 6
14 19
15 74
16 31
17 25
18 12
19
Distributed Representations of Words and Documents for Discriminating Similar Languages
13
20 1

About Marc Franco-Salvador

Marc Franco-Salvador is a scholar working on Artificial Intelligence, Applied Psychology and Computer Science Applications, having authored 24 papers that have together received 358 indexed citations. Recurring topics across this work include Topic Modeling (20 papers), Natural Language Processing Techniques (13 papers) and Text Readability and Simplification (7 papers). The work is most often cited by research in Artificial Intelligence (314 citations), Health Informatics (9 citations) and Safety Research (53 citations). Marc Franco-Salvador has collaborated with scholars based in Spain, Germany and United States. Frequent co-authors include Paolo Rosso, Manuel Montes-y-Gómez, Sanja Štajner, Parth Gupta, Roberto Navigli, Simone Paolo Ponzetto, Rafael E. Banchs, Thamar Solorio, Sudipta Kar and Luis A. Leiva. Their work appears in journals such as Knowledge-Based Systems, International Journal of Human-Computer Studies and Information Processing & Management.

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