Sriparna Saha
- Artificial Intelligence top 2%
- Molecular Biology
- Information Systems top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Pushpak BhattacharyyaAsif EkbalTulika SahaKanchan JhaShweta YadavAnkit KumarNaveen SainiSnehanshu Saha
- Topics
- Topic Modeling (28 papers)Hate Speech and Cyberbullying Detection (23 papers)Sentiment Analysis and Opinion Mining (16 papers)
- Partner nations
- IndiaSouth KoreaMalaysia
In The Last Decade
Sriparna Saha
104 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 768
- Molecular Biology 240
- Information Systems 158
- Radiology, Nuclear Medicine and Imaging 138
- Computer Vision and Pattern Recognition 117
Countries citing papers authored by Sriparna Saha
This map shows the geographic impact of Sriparna Saha'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 Sriparna Saha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sriparna Saha more than expected).
Fields of papers citing papers by Sriparna Saha
This network shows the impact of papers produced by Sriparna Saha. 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 Sriparna Saha. The network helps show where Sriparna Saha may publish in the future.
Co-authorship network of co-authors of Sriparna Saha
This figure shows the co-authorship network connecting the top 25 collaborators of Sriparna Saha. A scholar is included among the top collaborators of Sriparna Saha 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 Sriparna Saha. Sriparna Saha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 15 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 6 | |
| 12 | 4 | |
| 13 | 1 | |
| 14 | 9 | |
| 15 | 1 | |
| 16 | A GRU-based Fake News Prediction System: Working Notes for UrduFake-FIRE 2020. | 3 |
| 17 | Source Code Authorship Attribution using Stacked classifier. | 3 |
| 18 | Gender Age and Dialect Recognition using Tweets in a Deep Learning Framework - Notebook for FIRE 2019. | 7 |
| 19 | A Recurrent Neural Network Architecture for De-identifying Clinical Records. | 9 |
| 20 | ISOLATION AND CHARACTERIZATION OF BRUCELLA ABORTUS FROM BOVINES IN ANDAMANS | 0 |
About Sriparna Saha
Sriparna Saha is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 110 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (28 papers), Hate Speech and Cyberbullying Detection (23 papers) and Sentiment Analysis and Opinion Mining (16 papers). The work is most often cited by research in Artificial Intelligence (768 citations), Health Informatics (15 citations) and Information Systems (158 citations). Sriparna Saha has collaborated with scholars based in India, South Korea and Malaysia. Frequent co-authors include Pushpak Bhattacharyya, Asif Ekbal, Tulika Saha, Kanchan Jha, Shweta Yadav, Ankit Kumar, Naveen Saini, Snehanshu Saha, Aditya Kumar Patra and Gaurav Choudhary. Their work appears in journals such as PLoS ONE, Journal of Agricultural and Food Chemistry and Scientific Reports.
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.