Basant Agarwal

2.9k total citations
68 papers, 1.4k citations indexed

About

Basant Agarwal is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Basant Agarwal has authored 68 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 13 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Basant Agarwal's work include Sentiment Analysis and Opinion Mining (17 papers), Topic Modeling (13 papers) and Advanced Text Analysis Techniques (12 papers). Basant Agarwal is often cited by papers focused on Sentiment Analysis and Opinion Mining (17 papers), Topic Modeling (13 papers) and Advanced Text Analysis Techniques (12 papers). Basant Agarwal collaborates with scholars based in India, Australia and United Kingdom. Basant Agarwal's co-authors include Namita Mittal, Gauri Jain, Маниша Шарма, Sonal Garg, Heri Ramampiaro, Helge Langseth, Azizur Rahman, Alexander Gelbukh, Soujanya Poria and Sudha Morwal and has published in prestigious journals such as SHILAP Revista de lepidopterología, British Journal of Anaesthesia and Brain Behavior and Immunity.

In The Last Decade

Basant Agarwal

63 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Basant Agarwal India	22	920	438	231	185	102	68	1.4k
Wanli Zuo China	18	1.0k 1.1×	482 1.1×	124 0.5×	170 0.9×	124 1.2×	127	1.5k
Hasan Bulut Türkiye	15	872 0.9×	344 0.8×	299 1.3×	128 0.7×	165 1.6×	57	1.5k
Sameep Mehta India	17	483 0.5×	312 0.7×	177 0.8×	173 0.9×	168 1.6×	80	1.3k
Vaibhav Rupapara United States	13	597 0.6×	232 0.5×	95 0.4×	189 1.0×	92 0.9×	19	1.0k
Katarzyna Musiał Australia	20	738 0.8×	237 0.5×	169 0.7×	137 0.7×	159 1.6×	81	1.5k
Christos Makris Greece	18	409 0.4×	402 0.9×	239 1.0×	102 0.6×	112 1.1×	122	1.1k
Pasquale De Meo Italy	26	755 0.8×	652 1.5×	439 1.9×	354 1.9×	163 1.6×	95	2.0k
Juan D. Velásquez Chile	20	654 0.7×	432 1.0×	94 0.4×	177 1.0×	132 1.3×	71	1.3k
Paolo Torroni Italy	17	1.1k 1.2×	309 0.7×	120 0.5×	112 0.6×	110 1.1×	106	1.5k
Tien Thanh Nguyen Australia	21	567 0.6×	419 1.0×	101 0.4×	180 1.0×	211 2.1×	57	1.2k

Countries citing papers authored by Basant Agarwal

Since Specialization

Citations

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

Fields of papers citing papers by Basant Agarwal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Basant Agarwal

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

Agarwal, Basant, et al.. (2025). Hate Speech Detection: Leveraging LLM-GPT2 with Fine-Tuning and Multi-Shot Techniques. Procedia Computer Science. 258. 2817–2825.

Agarwal, Basant, et al.. (2024). Interactive Learning Through the Metaverse and its Impact on Primary Education. 1–8. 1 indexed citations

Pathak, Sunil, et al.. (2024). Improved diabetic retinopathy severity classification using squeeze-and-excitation and sparse light weight multi-level attention u-net with transfer learning from xception. Acta Diabetologica. 62(1). 95–112. 1 indexed citations

Agarwal, Basant, et al.. (2023). Early and Automated Diagnosis of Dysgraphia Using Machine Learning Approach. SN Computer Science. 4(5). 2 indexed citations

Agarwal, Basant, et al.. (2023). Analysing Misinformation Sharing Amongst College Students in India During COVID-19. Procedia Computer Science. 218. 671–685. 6 indexed citations

Agarwal, Basant, Mukesh Kumar Gupta, Harish Sharma, & Ramesh Chandra Poonia. (2022). Siamese-Based Architecture for Cross-Lingual Plagiarism Detection in English–Hindi Language Pairs. Big Data. 11(1). 48–58. 1 indexed citations

Agarwal, Basant, et al.. (2022). Diagnosis and Classification of Cancer Using Machine Learning Techniques. 1–5.

Sharma, Richa, Sudha Morwal, & Basant Agarwal. (2022). Named entity recognition using neural language model and CRF for Hindi language. Computer Speech & Language. 74. 101356–101356. 21 indexed citations

Kumar, Anupam, et al.. (2022). Texture Enhancement of Medical Images for Efficient Disease Diagnosis with Optimized Fractional Derivative Masks. Journal of Computational Biology. 29(6). 545–564. 2 indexed citations

10.

Saxena, Sameer, et al.. (2022). Comparative analysis between different edge detection techniques on mammogram images using PSNR and MSE. Journal of Information and Optimization Sciences. 43(2). 347–356. 8 indexed citations

11.

Aradhya, V. N. Manjunath, Mufti Mahmud, D. S. Guru, Basant Agarwal, & M. Shamim Kaiser. (2021). One-shot Cluster-Based Approach for the Detection of COVID–19 from Chest X–ray Images. Cognitive Computation. 13(4). 873–881. 37 indexed citations

12.

Sharma, Richa, Sudha Morwal, & Basant Agarwal. (2021). Entity-Extraction Using Hybrid Deep-Learning Approach for Hindi text. International Journal of Cognitive Informatics and Natural Intelligence. 15(3). 1–11. 1 indexed citations

13.

Agarwal, Basant, et al.. (2020). Sentiment analysis of social media response on the Covid19 outbreak. Brain Behavior and Immunity. 87. 136–137. 75 indexed citations

14.

Agarwal, Basant, Richi Nayak, Namita Mittal, & Srikanta Patnaik. (2020). Deep Learning-Based Approaches for Sentiment Analysis. Algorithms for intelligent systems. 42 indexed citations

15.

Saxena, Sameer, et al.. (2020). Boundary Detection to Segment the Pectoral Muscle from Digital Mammograms Images. International Journal of Engineering and Advanced Technology. 9(3). 1593–1603. 2 indexed citations

16.

Sharma, Richa, Sudha Morwal, Basant Agarwal, Ramesh Chandra, & Mohammad S. Khan. (2020). A deep neural network-based model for named entity recognition for Hindi language. Neural Computing and Applications. 32(20). 16191–16203. 32 indexed citations

17.

Jain, Gauri, Маниша Шарма, & Basant Agarwal. (2019). Spam detection in social media using convolutional and long short term memory neural network. Annals of Mathematics and Artificial Intelligence. 85(1). 21–44. 100 indexed citations

18.

Martín, Daniel, Joanne Howard, Basant Agarwal, et al.. (2016). Ebola virus disease: the UK critical care perspective. British Journal of Anaesthesia. 116(5). 590–596. 8 indexed citations

19.

Agarwal, Basant & Namita Mittal. (2013). Sentiment Classification using Rough Set based Hybrid Feature Selection. North American Chapter of the Association for Computational Linguistics. 115–119. 28 indexed citations

20.

Agarwal, Basant, Namita Mittal, & Erik Cambria. (2013). Enhancing Sentiment Classification Performance Using Bi-Tagged Phrases. National University of Singapore. 7817. 892–895. 17 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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