Ashraf Uddin
Impact in
-
- scientometrics and bibliometrics research
- Computer Science Applications top 10%
- Online Learning and Analytics
Papers in
-
- Sentiment Analysis and Opinion Mining 5
- Topic Modeling 5
- Text and Document Classification Technologies 4
- Natural Language Processing Techniques 2
-
- Web Data Mining and Analysis 3
- Co-authors
- Vivek Kumar Singh (22 shared papers)Rajesh Piryani (8 shared papers)Sumit Kumar Banshal (6 shared papers)David Pinto (3 shared papers)Khushboo Singhal (5 shared papers)Bishwajeet Pandey (1 shared paper)Teerath Das (1 shared paper)Tanesh Kumar (1 shared paper)
- Journals
- Scientometrics (4 papers)Current Science (3 papers)IETE Technical Review (2 papers)Journal of Scientometric Research (2 papers)Lecture notes in computer science (2 papers)
- Partner nations
- IndiaBangladeshMexico
In The Last Decade
Ashraf Uddin
28 papers receiving 487 citations
Peers
Comparison fields: 5 of 80
- Statistics, Probability and Uncertainty 74
- Computer Science Applications 56
- Artificial Intelligence 276
- Information Systems 143
- Management Science and Operations Research 57
Countries citing papers authored by Ashraf Uddin
This map shows the geographic impact of Ashraf Uddin'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 Ashraf Uddin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashraf Uddin more than expected).
Fields of papers citing papers by Ashraf Uddin
This network shows the impact of papers produced by Ashraf Uddin. 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 Ashraf Uddin. The network helps show where Ashraf Uddin may publish in the future.
Co-authors
The 9 scholars most cited alongside Ashraf Uddin, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 160 | |
| 2 | 2013 | 51 | |
| 3 | 2015 | 45 | |
| 4 | 2013 | 37 | |
| 5 | 2015 | 33 | |
| 6 | 2015 | 28 | |
| 7 | 2016 | 25 | |
| 8 | 2014 | 23 | |
| 9 | 2016 | 14 | |
| 10 | 2015 | 13 | |
| 11 | Measuring Research Output and Collaboration in South Asian Countries | 2014 | 13 |
| 12 | 2014 | 12 | |
| 13 | 2016 | 11 | |
| 14 | 2021 | 11 | |
| 15 | 2014 | 10 | |
| 16 | 2015 | 7 | |
| 17 | 2021 | 6 | |
| 18 | 2013 | 5 | |
| 19 | 2013 | 5 | |
| 20 | 2014 | 4 |
About Ashraf Uddin
Ashraf Uddin is a scholar working on Artificial Intelligence, Information Systems, Computer Science Applications, Statistics, Probability and Uncertainty and Economics and Econometrics, having authored 30 papers that have together received 532 indexed citations. Recurring topics across this work include Online Learning and Analytics (7 papers), scientometrics and bibliometrics research (6 papers), Sentiment Analysis and Opinion Mining (5 papers), Topic Modeling (5 papers), Text and Document Classification Technologies (4 papers), Web Data Mining and Analysis (3 papers), Natural Language Processing Techniques (2 papers) and COVID-19 Pandemic Impacts (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (74 citations), Computer Science Applications (56 citations), Artificial Intelligence (276 citations), Information Systems (143 citations) and Management Science and Operations Research (57 citations). Ashraf Uddin has collaborated with scholars based in India, Bangladesh and Mexico. Frequent co-authors include Vivek Kumar Singh, Rajesh Piryani, Sumit Kumar Banshal, David Pinto, Khushboo Singhal, Bishwajeet Pandey, Teerath Das, Tanesh Kumar and Md. Mehedi Hassan Onik. Their work appears in journals such as Scientometrics, Current Science, IETE Technical Review, Journal of Scientometric Research and Lecture notes in computer science.
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.