Sumit Kumar Banshal
Impact in
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- scientometrics and bibliometrics research
Papers in
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- Advanced Text Analysis Techniques 3
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- scientometrics and bibliometrics research 7
- Co-authors
- Vivek Kumar Singh (18 shared papers)Khushboo Singhal (5 shared papers)Pranab K. Muhuri (4 shared papers)Ashraf Uddin (6 shared papers)Aparna Basu (3 shared papers)Manoj Kumar Verma (1 shared paper)Mayank Yuvaraj (1 shared paper)Robert John (1 shared paper)
- Journals
- Scientometrics (4 papers)Current Science (4 papers)Library Hi Tech (1 paper)Online Information Review (1 paper)PLoS ONE (1 paper)
- Partner nations
- IndiaBangladeshUnited Kingdom
In The Last Decade
Sumit Kumar Banshal
28 papers receiving 301 citations
Peers
Comparison fields: 5 of 81
- Statistics, Probability and Uncertainty 89
- Health Informatics 7
- Communication 32
- Computer Science Applications 19
- Information Systems and Management 24
Countries citing papers authored by Sumit Kumar Banshal
This map shows the geographic impact of Sumit Kumar Banshal'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 Sumit Kumar Banshal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumit Kumar Banshal more than expected).
Fields of papers citing papers by Sumit Kumar Banshal
This network shows the impact of papers produced by Sumit Kumar Banshal. 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 Sumit Kumar Banshal. The network helps show where Sumit Kumar Banshal may publish in the future.
Co-authors
The 25 scholars most cited alongside Sumit Kumar Banshal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 42 | |
| 2 | 2022 | 30 | |
| 3 | 2020 | 29 | |
| 4 | 2017 | 25 | |
| 5 | 2020 | 24 | |
| 6 | 2016 | 23 | |
| 7 | 2022 | 16 | |
| 8 | 2019 | 14 | |
| 9 | 2017 | 14 | |
| 10 | 2024 | 14 | |
| 11 | 2018 | 12 | |
| 12 | 2020 | 12 | |
| 13 | 2014 | 11 | |
| 14 | 2018 | 10 | |
| 15 | 2015 | 7 | |
| 16 | 2020 | 6 | |
| 17 | 2024 | 4 | |
| 18 | 2022 | 4 | |
| 19 | 2014 | 4 | |
| 20 | 2015 | 4 |
About Sumit Kumar Banshal
Sumit Kumar Banshal is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty, Information Systems, Computer Science Applications and Sociology and Political Science, having authored 35 papers that have together received 321 indexed citations. Recurring topics across this work include scientometrics and bibliometrics research (7 papers), Online Learning and Analytics (6 papers), Smart Agriculture and AI (4 papers), Advanced Text Analysis Techniques (3 papers), Digital Marketing and Social Media (2 papers), Web visibility and informetrics (2 papers), Big Data and Business Intelligence (2 papers) and Network Security and Intrusion Detection (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (89 citations), Health Informatics (7 citations), Communication (32 citations), Computer Science Applications (19 citations) and Information Systems and Management (24 citations). Sumit Kumar Banshal has collaborated with scholars based in India, Bangladesh and United Kingdom. Frequent co-authors include Vivek Kumar Singh, Khushboo Singhal, Pranab K. Muhuri, Ashraf Uddin, Aparna Basu, Manoj Kumar Verma, Mayank Yuvaraj, Robert John, Amit K. Shukla and Philipp Mayr. Their work appears in journals such as Scientometrics, Current Science, Library Hi Tech, Online Information Review and PLoS ONE.
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.