Ringki Das
Impact in
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Topic Modeling
- Text and Document Classification Technologies
- Natural Language Processing Techniques
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- Multimodal Machine Learning Applications
- Video Analysis and Summarization
Papers in
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- Multimodal Machine Learning Applications 6
- Video Analysis and Summarization 2
- Human Pose and Action Recognition 2
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- Sentiment Analysis and Opinion Mining 4
- Text and Document Classification Technologies 3
- Advanced Text Analysis Techniques 1
- Natural Language Processing Techniques 1
- Journals
- Multimedia Tools and Applications (2 papers)ACM Computing Surveys (1 paper)Expert Systems with Applications (1 paper)ACM Transactions on Asian and Low-Resource Language Information Processing (1 paper)Procedia Computer Science (2 papers)
- Partner nations
- India
In The Last Decade
Ringki Das
7 papers receiving 202 citations
Ringki Das's Hit Papers
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 166
- Computer Vision and Pattern Recognition 43
- Experimental and Cognitive Psychology 27
- Signal Processing 15
- General Social Sciences 4
Countries citing papers authored by Ringki Das
This map shows the geographic impact of Ringki Das'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 Ringki Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ringki Das more than expected).
Fields of papers citing papers by Ringki Das
This network shows the impact of papers produced by Ringki Das. 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 Ringki Das. The network helps show where Ringki Das may publish in the future.
Co-authors
The 2 scholars most cited alongside Ringki Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges Hit paper breakdown → | 2023 | 138 |
| 2 | 2023 | 24 | |
| 3 | 2022 | 19 | |
| 4 | 2022 | 14 | |
| 5 | 2023 | 8 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 2 |
About Ringki Das
Ringki Das is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Social Psychology, Infectious Diseases and Organic Chemistry, having authored 7 papers that have together received 209 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (6 papers), Sentiment Analysis and Opinion Mining (4 papers), Text and Document Classification Technologies (3 papers), Video Analysis and Summarization (2 papers), Human Pose and Action Recognition (2 papers), Advanced Text Analysis Techniques (1 paper), Humor Studies and Applications (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (166 citations), Computer Vision and Pattern Recognition (43 citations), Experimental and Cognitive Psychology (27 citations), Signal Processing (15 citations) and General Social Sciences (4 citations). Ringki Das has collaborated with scholars based in India. Frequent co-authors include Thoudam Doren Singh and Sivaji Bandyopadhyay. Their work appears in journals such as Multimedia Tools and Applications, ACM Computing Surveys, Expert Systems with Applications, ACM Transactions on Asian and Low-Resource Language Information Processing and Procedia 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.