Vigneshwaran Muralidaran

431 total citations
7 papers, 216 citations indexed

About

Vigneshwaran Muralidaran is a scholar working on Artificial Intelligence, Communication and Radiological and Ultrasound Technology. According to data from OpenAlex, Vigneshwaran Muralidaran has authored 7 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 1 paper in Communication and 1 paper in Radiological and Ultrasound Technology. Recurrent topics in Vigneshwaran Muralidaran's work include Natural Language Processing Techniques (4 papers), Hate Speech and Cyberbullying Detection (3 papers) and Topic Modeling (2 papers). Vigneshwaran Muralidaran is often cited by papers focused on Natural Language Processing Techniques (4 papers), Hate Speech and Cyberbullying Detection (3 papers) and Topic Modeling (2 papers). Vigneshwaran Muralidaran collaborates with scholars based in United Kingdom, India and Ireland. Vigneshwaran Muralidaran's co-authors include Bharathi Raja Chakravarthi, John P. McCrae, Ruba Priyadharshini, Navya Jose, Shardul Suryawanshi, Elizabeth Sherly, José Antonio Garcí­a-Dí­az, Rahul Ponnusamy, Dawn Knight and ‪Irena Spasić and has published in prestigious journals such as Language Resources and Evaluation, Natural Language Engineering and JMIR Formative Research.

In The Last Decade

Vigneshwaran Muralidaran

5 papers receiving 150 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vigneshwaran Muralidaran United Kingdom 5 207 26 24 16 14 7 216
Navya Jose India 5 188 0.9× 21 0.8× 27 1.1× 12 0.8× 11 0.8× 5 215
Alex Marin United States 9 184 0.9× 24 0.9× 25 1.0× 19 1.2× 8 0.6× 20 208
Rahul Ponnusamy India 8 172 0.8× 16 0.6× 19 0.8× 8 0.5× 27 1.9× 15 178
Prasanna Kumar Kumaresan India 8 177 0.9× 20 0.8× 17 0.7× 6 0.4× 24 1.7× 16 184
Marco Del Tredici Netherlands 5 137 0.7× 23 0.9× 13 0.5× 8 0.5× 9 0.6× 13 157
Ilia Markov Mexico 10 207 1.0× 56 2.2× 22 0.9× 11 0.7× 17 1.2× 38 249
Hala Mulki Türkiye 8 213 1.0× 40 1.5× 30 1.3× 4 0.3× 22 1.6× 12 224
Alessandra Teresa Cignarella Italy 9 180 0.9× 24 0.9× 16 0.7× 6 0.4× 13 0.9× 19 200
Qinlan Shen United States 8 201 1.0× 21 0.8× 34 1.4× 39 2.4× 6 0.4× 13 234
Andrew Caines United Kingdom 9 163 0.8× 54 2.1× 8 0.3× 12 0.8× 6 0.4× 40 226

Countries citing papers authored by Vigneshwaran Muralidaran

Since Specialization
Citations

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

Fields of papers citing papers by Vigneshwaran Muralidaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vigneshwaran Muralidaran

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

All Works

7 of 7 papers shown
1.
Bennett, Verity, ‪Irena Spasić, Vigneshwaran Muralidaran, et al.. (2024). Assessing the Feasibility of Using Parents’ Social Media Conversations to Inform Burn First Aid Interventions: Mixed Methods Study. JMIR Formative Research. 8. e48695–e48695.
2.
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
3.
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
4.
Chakravarthi, Bharathi Raja & Vigneshwaran Muralidaran. (2021). Findings of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion. 61–72. 76 indexed citations
5.
Muralidaran, Vigneshwaran, ‪Irena Spasić, & Dawn Knight. (2020). A systematic review of unsupervised approaches to grammar induction. Natural Language Engineering. 27(6). 647–689. 4 indexed citations
6.
Chakravarthi, Bharathi Raja, Ruba Priyadharshini, Vigneshwaran Muralidaran, et al.. (2020). Overview of the track on Sentiment Analysis for Dravidian Languages in Code-Mixed Text. 21–24. 69 indexed citations
7.
Muralidaran, Vigneshwaran, et al.. (2016). Non-decreasing Sub-modular Function for Comprehensible Summarization. 94–101. 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.

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