Aline Paes

655 total citations
72 papers, 284 citations indexed

About

Aline Paes is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Aline Paes has authored 72 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Artificial Intelligence, 12 papers in Information Systems and 11 papers in Computer Networks and Communications. Recurrent topics in Aline Paes's work include Sentiment Analysis and Opinion Mining (16 papers), Topic Modeling (16 papers) and Natural Language Processing Techniques (12 papers). Aline Paes is often cited by papers focused on Sentiment Analysis and Opinion Mining (16 papers), Topic Modeling (16 papers) and Natural Language Processing Techniques (12 papers). Aline Paes collaborates with scholars based in Brazil, France and United States. Aline Paes's co-authors include Daniel de Oliveira, Gerson Zaverucha, Flávia Bernardini, Cláudio Tinoco Mesquita, Flávio Luiz Seixas, Esteban Clua, Alexandre Plastino, Antônio A. de A. Rocha, Vı́tor Santos Costa and Leonardo Murta and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Sensors.

In The Last Decade

Aline Paes

54 papers receiving 270 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aline Paes Brazil 8 143 53 50 44 32 72 284
Mohd Nor Akmal Khalid Japan 10 154 1.1× 95 1.8× 55 1.1× 40 0.9× 20 0.6× 72 352
Pavel Kucherbaev Italy 7 164 1.1× 29 0.5× 54 1.1× 17 0.4× 19 0.6× 8 372
Meng Chen China 10 149 1.0× 65 1.2× 20 0.4× 27 0.6× 87 2.7× 39 499
Juan Carlos Nieves Sweden 11 250 1.7× 27 0.5× 30 0.6× 8 0.2× 12 0.4× 72 403
Ricardo Santos Portugal 10 75 0.5× 49 0.9× 16 0.3× 10 0.2× 46 1.4× 31 246
Nicolas Sabouret France 8 116 0.8× 37 0.7× 51 1.0× 6 0.1× 47 1.5× 28 207
Theodore Kotsilieris Greece 10 53 0.4× 23 0.4× 56 1.1× 7 0.2× 12 0.4× 34 276
Kasthuri Jayarajah Singapore 11 72 0.5× 36 0.7× 28 0.6× 21 0.5× 6 0.2× 33 333
Umang Gupta India 8 260 1.8× 28 0.5× 39 0.8× 7 0.2× 37 1.2× 25 451
Sagar Joglekar United Kingdom 10 64 0.4× 72 1.4× 26 0.5× 12 0.3× 19 0.6× 22 241

Countries citing papers authored by Aline Paes

Since Specialization
Citations

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

Fields of papers citing papers by Aline Paes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aline Paes

This figure shows the co-authorship network connecting the top 25 collaborators of Aline Paes. A scholar is included among the top collaborators of Aline Paes 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 Aline Paes. Aline Paes 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.
Paes, Aline, et al.. (2025). Towards Robust Neurosymbolic Relational Learning. City Research Online (City University London). 1–8.
2.
Oliveira, Daniel de, et al.. (2024). Exploring Portuguese Hate Speech Detection with Transformers. 1 indexed citations
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Plastino, Alexandre, et al.. (2024). Less is more: Pruning BERTweet architecture in Twitter sentiment analysis. Information Processing & Management. 61(4). 103688–103688. 4 indexed citations
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Clua, Esteban, et al.. (2023). Encoding feature set information in heterogeneous graph neural networks for game provenance. Applied Intelligence. 53(23). 29024–29042. 1 indexed citations
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Paes, Aline, et al.. (2023). Word embeddings-based transfer learning for boosted relational dependency networks. Machine Learning. 113(3). 1269–1302. 4 indexed citations
11.
Oliveira, Daniel de, et al.. (2023). LHTR.br: em Busca de um Conjunto Anotado de Textos Manuscritos em Português. 13–24. 1 indexed citations
12.
Paes, Aline, et al.. (2023). Masked transformer through knowledge distillation for unsupervised text style transfer. Natural Language Engineering. 30(5). 973–1008. 3 indexed citations
13.
Plastino, Alexandre, et al.. (2023). Sentiment analysis in Portuguese tweets: an evaluation of diverse word representation models. Language Resources and Evaluation. 58(1). 223–272. 2 indexed citations
14.
Paes, Aline, et al.. (2022). Sentiment analysis in tweets: an assessment study from classical to modern word representation models. Data Mining and Knowledge Discovery. 37(1). 318–380. 9 indexed citations
15.
Pacitti, Esther, et al.. (2021). Provenance-and machine learning-based recommendation of parameter values in scientific workflows. PeerJ Computer Science. 7. e606–e606. 1 indexed citations
16.
Silva, Filipe, et al.. (2021). Online Deep Learning Hyperparameter Tuning based on Provenance Analysis. Journal of Information and Data Management. 12(5). 4 indexed citations
17.
Paes, Aline, et al.. (2016). SiAPP: An Information System for Crime Analytics Based on Logical Relational Learning. IEEE International Conference on Cloud Computing Technology and Science. 23. 2 indexed citations
18.
Revoredo, Kate, et al.. (2014). Syntactic Compression of Description Logics Terminologies. 180–185.
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Revoredo, Kate, et al.. (2013). Terminology Learning through Taxonomy Discovery. 7094. 169–174. 2 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.

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2026