Óscar Araque

1.5k total citations · 1 hit paper
29 papers, 998 citations indexed

About

Óscar Araque is a scholar working on Artificial Intelligence, Sociology and Political Science and Information Systems. According to data from OpenAlex, Óscar Araque has authored 29 papers receiving a total of 998 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 7 papers in Sociology and Political Science and 7 papers in Information Systems. Recurrent topics in Óscar Araque's work include Sentiment Analysis and Opinion Mining (19 papers), Hate Speech and Cyberbullying Detection (9 papers) and Advanced Text Analysis Techniques (8 papers). Óscar Araque is often cited by papers focused on Sentiment Analysis and Opinion Mining (19 papers), Hate Speech and Cyberbullying Detection (9 papers) and Advanced Text Analysis Techniques (8 papers). Óscar Araque collaborates with scholars based in Spain, Netherlands and Italy. Óscar Araque's co-authors include Carlos Á. Iglesias, J. Fernando Sánchez-Rada, Ganggao Zhu, Lorenzo Gatti, Kyriaki Kalimeri, Marco Guerini, Jacopo Staiano, Álvaro Carrera, Miriam Fernández and Harith Alani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Óscar Araque

28 papers receiving 944 citations

Hit Papers

Enhancing deep learning sentiment analysis with ensemble ... 2017 2026 2020 2023 2017 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Enhancing deep learning sentiment analysis with ensemble techniques in social applications
    2017 413 citations Óscar Araque, J. Fernando Sánchez-Rada et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Óscar Araque Spain 11 752 298 282 68 64 29 998
Kumar Ravi India 14 881 1.2× 303 1.0× 203 0.7× 50 0.7× 73 1.1× 28 1.3k
Arturo Montejo‐Ráez Spain 13 732 1.0× 266 0.9× 147 0.5× 53 0.8× 28 0.4× 58 968
Marco Viviani Italy 17 297 0.4× 287 1.0× 342 1.2× 33 0.5× 50 0.8× 47 764
Isabelle Augenstein Denmark 22 1.3k 1.8× 308 1.0× 386 1.4× 48 0.7× 60 0.9× 88 1.6k
Yohan Jo United States 12 745 1.0× 227 0.8× 142 0.5× 34 0.5× 28 0.4× 31 1.0k
Jiepu Jiang United States 14 341 0.5× 410 1.4× 120 0.4× 60 0.9× 34 0.5× 45 766
Sunil Saumya India 11 495 0.7× 232 0.8× 425 1.5× 23 0.3× 39 0.6× 34 796
Marouane Birjali Morocco 11 578 0.8× 192 0.6× 116 0.4× 89 1.3× 23 0.4× 16 808
Francisco P. Romero Spain 12 493 0.7× 307 1.0× 136 0.5× 34 0.5× 42 0.7× 42 769

Countries citing papers authored by Óscar Araque

Since Specialization
Citations

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

Fields of papers citing papers by Óscar Araque

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Óscar Araque

This figure shows the co-authorship network connecting the top 25 collaborators of Óscar Araque. A scholar is included among the top collaborators of Óscar Araque 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 Óscar Araque. Óscar Araque 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.
Araque, Óscar, et al.. (2023). A Toxic Style Transfer Method Based on the Delete–Retrieve–Generate Framework Exploiting Toxic Lexicon Semantic Similarity. Applied Sciences. 13(15). 8590–8590. 1 indexed citations
2.
Araque, Óscar, et al.. (2023). What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric. Research Repository (Delft University of Technology). 7 indexed citations
3.
Araque, Óscar, et al.. (2023). Contextualization of a Radical Language Detection System Through Moral Values and Emotions. IEEE Access. 11. 119634–119646.
4.
Araque, Óscar, J. Fernando Sánchez-Rada, & Carlos Á. Iglesias. (2022). GSITK: A sentiment analysis framework for agile replication and development. SoftwareX. 17. 100921–100921. 10 indexed citations
5.
Araque, Óscar, et al.. (2021). GSI-UPM at IberLEF2021: Emotion Analysis of Spanish Tweets by Fine-tuning the XLM-RoBERTa Language Model.. 16–26. 3 indexed citations
6.
Araque, Óscar & Carlos Á. Iglesias. (2021). An Ensemble Method for Radicalization and Hate Speech Detection Online Empowered by Sentic Computing. Cognitive Computation. 14(1). 48–61. 25 indexed citations
7.
Carrera, Álvaro, et al.. (2020). JAICOB: A Data Science Chatbot. IEEE Access. 8. 180672–180680. 30 indexed citations
8.
Araque, Óscar, et al.. (2020). Radical Text Detection based on Stylometry. 524–531. 2 indexed citations
9.
Araque, Óscar, et al.. (2020). On the use of Jargon and Word Embeddings to Explore Subculture within the Reddit’s Manosphere. 221–230. 16 indexed citations
10.
Araque, Óscar, et al.. (2019). A framework for fake review detection in online consumer electronics retailers. Information Processing & Management. 56(4). 1234–1244. 188 indexed citations
11.
Sánchez-Rada, J. Fernando, Óscar Araque, & Carlos Á. Iglesias. (2019). Senpy: A framework for semantic sentiment and emotion analysis services. Knowledge-Based Systems. 190. 105193–105193. 4 indexed citations
12.
Araque, Óscar, Lorenzo Gatti, Jacopo Staiano, & Marco Guerini. (2019). UPM Digital Archive (Technical University of Madrid). 38 indexed citations
13.
Araque, Óscar, Lorenzo Gatti, & Kyriaki Kalimeri. (2019). MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction. University of Twente Research Information. 1 indexed citations
14.
Araque, Óscar, et al.. (2018). An Emotion Aware Task Automation Architecture Based on Semantic Technologies for Smart Offices. Sensors. 18(5). 1499–1499. 14 indexed citations
15.
Araque, Óscar, et al.. (2018). A Cognitive Agent for Mining Bugs Reports, Feature Suggestions and Sentiment in a Mobile Application Store. Archivo Digital UPM (Universidad Politécnica de Madrid). 6 indexed citations
16.
Suárez, Daniel, Óscar Araque, & Carlos Á. Iglesias. (2018). How Well Do Spaniards Sleep? Analysis of Sleep Disorders Based on Twitter Mining. 17. 11–18. 3 indexed citations
17.
Araque, Óscar, Ganggao Zhu, & Carlos Á. Iglesias. (2018). A semantic similarity-based perspective of affect lexicons for sentiment analysis. Knowledge-Based Systems. 165. 346–359. 109 indexed citations
18.
Araque, Óscar, Marco Guerini, Carlo Strapparava, & Carlos Á. Iglesias. (2017). Neural domain adaptation of sentiment lexicons. Institutional Research Information System (Università degli Studi di Trento). 105–110. 6 indexed citations
19.
20.
Sánchez-Rada, J. Fernando, et al.. (2016). Senpy: A Pragmatic Linked Sentiment Analysis Framework. 1240. 735–742. 5 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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