This map shows the geographic impact of Ferran Plà'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 Ferran Plà with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ferran Plà more than expected).
This network shows the impact of papers produced by Ferran Plà. 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 Ferran Plà. The network helps show where Ferran Plà may publish in the future.
Co-authorship network of co-authors of Ferran Plà
This figure shows the co-authorship network connecting the top 25 collaborators of Ferran Plà.
A scholar is included among the top collaborators of Ferran Plà 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 Ferran Plà. Ferran Plà 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
1.
González, José Ángel, et al.. (2020). ELiRF-UPV at TASS 2020: TWilBERT for Sentiment Analysis and Emotion Detection in Spanish Tweets.. 179–186.6 indexed citations
2.
González, José Ángel, et al.. (2019). Aggressiveness Detection through Deep Learning Approaches.. 544–549.1 indexed citations
3.
González, José Ángel, et al.. (2019). ELiRF-UPV at IroSvA: Transformer Encoders for Spanish Irony Detection.. 278–284.6 indexed citations
4.
González, José Ángel, et al.. (2019). ELiRF-UPV at TASS 2019: Transformer Encoders for Twitter Sentiment Analysis in Spanish.. 571–578.2 indexed citations
Plà, Ferran, et al.. (2018). ELiRF-UPV en TASS 2018: Categorización Emocional de Noticias(ELiRF-UPV at TASS 2018: Emotional Categorization of News Articles).. 103–109.1 indexed citations
8.
González, José Ángel, et al.. (2017). ELiRF-UPV at IberEval 2017: Classification Of Spanish Election Tweets (COSET).. 55–60.1 indexed citations
Plà, Ferran, et al.. (2014). ELiRF-UPV en TweetLID: Identificación del Idioma en Twitter.. 35–38.3 indexed citations
12.
Plà, Ferran & Lluís-F. Hurtado. (2014). Political Tendency Identification in Twitter using Sentiment Analysis Techniques. 183–192.33 indexed citations
13.
Ponomareva, Natalia, Paolo Rosso, Ferran Plà, & Antonio Molina. (2007). Conditional Random Fields vs. Hidden Markov Models in a biomedical Named Entity Recognition task.19 indexed citations
14.
Molina‐Díaz, Antonio, Ferran Plà, & Encarna Segarra. (2004). WSD system based on specialized Hidden Markov Model (upv-shmm-eaw). Meeting of the Association for Computational Linguistics. 171–174.3 indexed citations
Molina‐Díaz, Antonio, et al.. (2003). 3LB-SAT : una herramienta de anotación semántica. Procesamiento del lenguaje natural. 31(31). 193–200.
17.
Molina, Antonio & Ferran Plà. (2002). Shallow parsing using specialized hmms. Journal of Machine Learning Research. 2(4). 595–613.51 indexed citations
18.
Plà, Ferran, et al.. (2001). Evaluación de un etiquetador morfosintáctico basado en bigramas especializados para el castellano. Procesamiento del lenguaje natural. 27(27). 215–221.1 indexed citations
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.