Saloni Dash
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
Papers in
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- Hate Speech and Cyberbullying Detection 3
- Machine Learning in Healthcare 3
- Privacy-Preserving Technologies in Data 3
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- Misinformation and Its Impacts 5
- Co-authors
- Isabelle Guyon (5 shared papers)Kristin P. Bennett (5 shared papers)Amit Sharma (1 shared paper)Vineeth N Balasubramanian (1 shared paper)Joyojeet Pal (3 shared papers)Karan Bhanot (2 shared papers)John Erickson (1 shared paper)Emma S. Spiro (1 shared paper)
- Journals
- Neurocomputing (1 paper)Lecture notes in computer science (1 paper)Lecture notes in business information processing (1 paper)Proceedings of the International AAAI Conference on Web and Social Media (2 papers)2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)
- Partner nations
- United StatesIndiaFrance
In The Last Decade
Saloni Dash
10 papers receiving 218 citations
Peers
Comparison fields: 5 of 64
- Health Informatics 17
- Health Information Management 25
- Artificial Intelligence 151
- Communication 15
- Management Science and Operations Research 22
Countries citing papers authored by Saloni Dash
This map shows the geographic impact of Saloni Dash'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 Saloni Dash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saloni Dash more than expected).
Fields of papers citing papers by Saloni Dash
This network shows the impact of papers produced by Saloni Dash. 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 Saloni Dash. The network helps show where Saloni Dash may publish in the future.
Co-authors
The 10 scholars most cited alongside Saloni Dash, 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 | 2020 | 110 | |
| 2 | 2022 | 28 | |
| 3 | 2020 | 28 | |
| 4 | 2022 | 17 | |
| 5 | 2019 | 15 | |
| 6 | 2020 | 12 | |
| 7 | 2022 | 5 | |
| 8 | 2021 | 4 | |
| 9 | 2024 | 1 | |
| 10 | 2022 | 1 | |
| 11 | 2025 | 0 |
About Saloni Dash
Saloni Dash is a scholar working on Artificial Intelligence, Sociology and Political Science, Communication, Signal Processing and Molecular Biology, having authored 11 papers that have together received 221 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (5 papers), Hate Speech and Cyberbullying Detection (3 papers), Machine Learning in Healthcare (3 papers), Privacy-Preserving Technologies in Data (3 papers), Social Media and Politics (3 papers), Time Series Analysis and Forecasting (2 papers), Spam and Phishing Detection (1 paper) and Psychology of Moral and Emotional Judgment (1 paper). The work is most often cited by research in Health Informatics (17 citations), Health Information Management (25 citations), Artificial Intelligence (151 citations), Communication (15 citations) and Management Science and Operations Research (22 citations). Saloni Dash has collaborated with scholars based in United States, India and France. Frequent co-authors include Isabelle Guyon, Kristin P. Bennett, Amit Sharma, Vineeth N Balasubramanian, Joyojeet Pal, Karan Bhanot, John Erickson, Emma S. Spiro, Ramaravind Kommiya Mothilal and Soham De. Their work appears in journals such as Neurocomputing, Lecture notes in computer science, Lecture notes in business information processing, Proceedings of the International AAAI Conference on Web and Social Media and 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
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.