Ruba Priyadharshini

1.3k total citations
28 papers, 596 citations indexed

About

Ruba Priyadharshini is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Communication. According to data from OpenAlex, Ruba Priyadharshini has authored 28 papers receiving a total of 596 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Communication. Recurrent topics in Ruba Priyadharshini's work include Hate Speech and Cyberbullying Detection (16 papers), Topic Modeling (11 papers) and Natural Language Processing Techniques (11 papers). Ruba Priyadharshini is often cited by papers focused on Hate Speech and Cyberbullying Detection (16 papers), Topic Modeling (11 papers) and Natural Language Processing Techniques (11 papers). Ruba Priyadharshini collaborates with scholars based in India, Ireland and Sri Lanka. Ruba Priyadharshini's co-authors include Bharathi Raja Chakravarthi, John P. McCrae, Sajeetha Thavareesan, Rahul Ponnusamy, Navya Jose, Elizabeth Sherly, Prasanna Kumar Kumaresan, Vigneshwaran Muralidaran, Shardul Suryawanshi and D. Thenmozhi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and Computer Speech & Language.

In The Last Decade

Ruba Priyadharshini

28 papers receiving 466 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ruba Priyadharshini India	17	572	74	68	48	38	28	596
Sajeetha Thavareesan Sri Lanka	11	467 0.8×	46 0.6×	69 1.0×	34 0.7×	36 0.9×	16	491
Shardul Suryawanshi Ireland	6	271 0.5×	35 0.5×	38 0.6×	35 0.7×	43 1.1×	9	287
Elena Cabrio France	11	399 0.7×	41 0.6×	109 1.6×	31 0.6×	39 1.0×	58	442
Sandip Modha India	11	542 0.9×	100 1.4×	109 1.6×	80 1.7×	42 1.1×	24	559
Syed Sarfaraz Akhtar India	6	267 0.5×	32 0.4×	46 0.7×	40 0.8×	14 0.4×	11	282
Mihael Arčan Ireland	12	415 0.7×	12 0.2×	52 0.8×	28 0.6×	25 0.7×	52	434
Ibrahim Abu Farha United Kingdom	9	480 0.8×	18 0.2×	77 1.1×	21 0.4×	27 0.7×	11	511
Ashwin Rajadesingan United States	5	282 0.5×	65 0.9×	146 2.1×	32 0.7×	91 2.4×	10	398
Flor Miriam Plaza-del-Arco Spain	10	361 0.6×	50 0.7×	70 1.0×	82 1.7×	28 0.7×	34	397
Mladen Karan Croatia	11	359 0.6×	22 0.3×	72 1.1×	25 0.5×	26 0.7×	27	414

Countries citing papers authored by Ruba Priyadharshini

Since Specialization

Citations

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

Fields of papers citing papers by Ruba Priyadharshini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruba Priyadharshini

This figure shows the co-authorship network connecting the top 25 collaborators of Ruba Priyadharshini. A scholar is included among the top collaborators of Ruba Priyadharshini 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 Ruba Priyadharshini. Ruba Priyadharshini 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

Priyadharshini, Ruba, et al.. (2025). Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective setting. SHILAP Revista de lepidopterología. 11. 100152–100152. 1 indexed citations

Kumaresan, Prasanna Kumar, Rahul Ponnusamy, Ruba Priyadharshini, Paul Buitelaar, & Bharathi Raja Chakravarthi. (2023). Homophobia and transphobia detection for low-resourced languages in social media comments. 5. 100041–100041. 7 indexed citations

Chakravarthi, Bharathi Raja, et al.. (2023). Detecting abusive comments at a fine-grained level in a low-resource language. 3. 100006–100006. 11 indexed citations

Subramanian, Malliga, et al.. (2022). An analysis of machine learning models for sentiment analysis of Tamil code-mixed data. Computer Speech & Language. 76. 101407–101407. 22 indexed citations

Kumar, M. Anand, et al.. (2022). Overview of the Shared Task on Machine Translation in Dravidian Languages. 271–278. 2 indexed citations

Priyadharshini, Ruba, et al.. (2022). The Best of both Worlds: Dual Channel Language modeling for Hope Speech Detection in low-resourced Kannada. 127–135. 3 indexed citations

Chakravarthi, Bharathi Raja, et al.. (2022). Offensive language identification in dravidian languages using MPNet and CNN. International Journal of Information Management Data Insights. 3(1). 100151–100151. 16 indexed citations

Chakravarthi, Bharathi Raja, Vigneshwaran Muralidaran, Ruba Priyadharshini, et al.. (2022). Overview of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion. 378–388. 16 indexed citations

Chakravarthi, Bharathi Raja, Ruba Priyadharshini, D. Thenmozhi, et al.. (2022). Overview of The Shared Task on Homophobia and Transphobia Detection in Social Media Comments. 369–377. 7 indexed citations

10.

Chakravarthi, Bharathi Raja, Ruba Priyadharshini, Vigneshwaran Muralidaran, et al.. (2022). DravidianCodeMix: sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text. Language Resources and Evaluation. 56(3). 765–806. 50 indexed citations

11.

Thenmozhi, D., et al.. (2022). Findings of the Shared Task on Emotion Analysis in Tamil. 279–285. 42 indexed citations

12.

Subramanian, Malliga, et al.. (2022). Offensive language detection in Tamil YouTube comments by adapters and cross-domain knowledge transfer. Computer Speech & Language. 76. 101404–101404. 29 indexed citations

13.

Chakravarthi, Bharathi Raja, et al.. (2022). How can we detect Homophobia and Transphobia? Experiments in a multilingual code-mixed setting for social media governance. International Journal of Information Management Data Insights. 2(2). 100119–100119. 13 indexed citations

14.

Chakravarthi, Bharathi Raja, et al.. (2021). Findings of the Shared Task on Machine Translation in Dravidian languages. 119–125. 5 indexed citations

15.

Ponnusamy, Rahul, et al.. (2021). IIITK@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion in Tamil , Malayalam and English. 197–203. 30 indexed citations

16.

Priyadharshini, Ruba, et al.. (2021). IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian Languages. 187–194. 24 indexed citations

17.

Chakravarthi, Bharathi Raja, Ruba Priyadharshini, Navya Jose, et al.. (2021). Findings of the Shared Task on Offensive Language Identification in Tamil, Malayalam, and Kannada. 133–145. 27 indexed citations

18.

Priyadharshini, Ruba, et al.. (2020). KanCMD: Kannada CodeMixed Dataset for Sentiment Analysis and Offensive Language Detection. 54–63. 42 indexed citations

19.

Chakravarthi, Bharathi Raja, et al.. (2019). Multilingual multimodal machine translation for Dravidian languages utilizing phonetic transcription. Arrow@dit (Dublin Institute of Technology). 56–63. 18 indexed citations

20.

Ranjan, Prakash, et al.. (2016). A comparative study on code-mixed data of Indian social media vs formal text. 608–611. 18 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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