Oana Cocarascu

709 total citations
23 papers, 275 citations indexed

About

Oana Cocarascu is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Oana Cocarascu has authored 23 papers receiving a total of 275 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Information Systems and 3 papers in Sociology and Political Science. Recurrent topics in Oana Cocarascu's work include Topic Modeling (15 papers), Natural Language Processing Techniques (5 papers) and Software Engineering Research (4 papers). Oana Cocarascu is often cited by papers focused on Topic Modeling (15 papers), Natural Language Processing Techniques (5 papers) and Software Engineering Research (4 papers). Oana Cocarascu collaborates with scholars based in United Kingdom, Serbia and Spain. Oana Cocarascu's co-authors include Francesca Toni, Antonio Rago, Andreas Vlachos, James Thorne, Christos Christodoulopoulos, Arpit Mittal, Christos Bechlivanidis, David A. Lagnado, Michael Schlichtkrull and Zhijiang Guo and has published in prestigious journals such as Artificial Intelligence, Computational Linguistics and Journal of Artificial Intelligence Research.

In The Last Decade

Oana Cocarascu

21 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Oana Cocarascu United Kingdom	10	237	84	46	13	12	23	275
Prafulla Bafna India	8	182 0.8×	83 1.0×	20 0.4×	8 0.6×	12 1.0×	27	252
Liliana Chanona-Hernández Mexico	6	199 0.8×	73 0.9×	29 0.6×	7 0.5×	11 0.9×	17	276
Davide Ceolin Netherlands	8	103 0.4×	64 0.8×	80 1.7×	23 1.8×	10 0.8×	33	182
Lena Dankin Israel	7	276 1.2×	89 1.1×	22 0.5×	10 0.8×	12 1.0×	13	310
Anh-Cuong Le Vietnam	8	254 1.1×	61 0.7×	35 0.8×	19 1.5×	23 1.9×	32	303
Raquel Martínez Spain	8	145 0.6×	96 1.1×	51 1.1×	22 1.7×	22 1.8×	16	250
Ade Romadhony Indonesia	9	232 1.0×	97 1.2×	23 0.5×	14 1.1×	20 1.7×	65	288
Lavanya Elluri United States	9	91 0.4×	106 1.3×	74 1.6×	31 2.4×	8 0.7×	23	213
Surya Kallumadi United States	5	129 0.5×	74 0.9×	26 0.6×	12 0.9×	16 1.3×	18	209
V. S. Anoop India	8	99 0.4×	57 0.7×	20 0.4×	11 0.8×	13 1.1×	20	184

Countries citing papers authored by Oana Cocarascu

Since Specialization

Citations

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

Fields of papers citing papers by Oana Cocarascu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oana Cocarascu

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

All Works

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20 of 20 papers shown

Rago, Antonio, et al.. (2025). Argumentative review aggregation and dialogical explanations. Artificial Intelligence. 340. 104291–104291. 1 indexed citations

Rodrigues, Odinaldo, et al.. (2024). Identifying Reasons for Bias: An Argumentation-Based Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 38(19). 21664–21672.

Rodrigues, Odinaldo, et al.. (2024). Bias Mitigation Methods: Applicability, Legality, and Recommendations for Development. Journal of Artificial Intelligence Research. 81. 1043–1078.

Schlichtkrull, Michael, Yulong Chen, Zhenyun Deng, et al.. (2024). The Automated Verification of Textual Claims (AVeriTeC) Shared Task. 1–26. 1 indexed citations

Gupta, Vivek, et al.. (2024). ChartCheck: Explainable Fact-Checking over Real-World Chart Images. 13921–13937. 1 indexed citations

Cocarascu, Oana, et al.. (2023). Investigating the Legality of Bias Mitigation Methods in the United Kingdom. IEEE Technology and Society Magazine. 42(4). 87–94. 1 indexed citations

Schlichtkrull, Michael, et al.. (2023). Multimodal Automated Fact-Checking: A Survey. Queen Mary Research Online (Queen Mary University of London). 5430–5448. 5 indexed citations

Čyras, Kristijonas, Oana Cocarascu, Francis Ruiz, et al.. (2023). ROAD2H: Development and evaluation of an open‐source explainable artificial intelligence approach for managing co‐morbidity and clinical guidelines. Learning Health Systems. 8(2). e10391–e10391. 3 indexed citations

Gupta, Vivek, et al.. (2023). Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data. 15391–15405. 5 indexed citations

10.

Cocarascu, Oana, et al.. (2023). Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking. 399–414. 6 indexed citations

11.

Black, Elizabeth, Martim Brandão, Oana Cocarascu, et al.. (2022). Reasoning and interaction for social artificial intelligence. AI Communications. 35(4). 309–325. 3 indexed citations

12.

Cocarascu, Oana, et al.. (2022). PubHealthTab: A Public Health Table-based Dataset for Evidence-based Fact Checking. Research Portal (King's College London). 1–16. 6 indexed citations

13.

Guo, Zhijiang, Michael Schlichtkrull, James Thorne, et al.. (2021). The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task. Queen Mary Research Online (Queen Mary University of London). 1–13. 42 indexed citations

14.

Rago, Antonio, Oana Cocarascu, Christos Bechlivanidis, David A. Lagnado, & Francesca Toni. (2021). Argumentative explanations for interactive recommendations. Artificial Intelligence. 296. 103506–103506. 28 indexed citations

15.

Rago, Antonio, Oana Cocarascu, Christos Bechlivanidis, & Francesca Toni. (2020). Argumentation as a Framework for Interactive Explanations for Recommendations. Spiral (Imperial College London). 805–815. 16 indexed citations

16.

Thorne, James, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, & Arpit Mittal. (2019). The FEVER2.0 Shared Task. 1–6. 30 indexed citations

17.

Cocarascu, Oana, Antonio Rago, & Francesca Toni. (2019). Extracting Dialogical Explanations for Review Aggregations with Argumentative Dialogical Agents. Spiral (Imperial College London). 1261–1269. 17 indexed citations

18.

Cocarascu, Oana & Francesca Toni. (2018). Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets. Computational Linguistics. 44(4). 833–858. 17 indexed citations

19.

Rago, Antonio, Oana Cocarascu, & Francesca Toni. (2018). Argumentation-Based Recommendations: Fantastic Explanations and How to Find Them. Research Portal (King's College London). 1949–1955. 35 indexed citations

20.

Cocarascu, Oana & Francesca Toni. (2016). Detecting deceptive reviews using Argumentation. Spiral (Imperial College London). 1–8. 12 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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