Shahbaz Syed
- Artificial Intelligence top 5%
- Sociology and Political Science top 10%
- Health top 10%
- Cellular and Molecular Neuroscience
- Communication top 5%
- Co-authors
- Hans RosenbergSalim RezaieBenno SteinMartin PotthastHenning WachsmuthMichael VölskeStephen W.P. KempAubrey A. Webb
- Topics
- Topic Modeling (13 papers)Natural Language Processing Techniques (11 papers)Advanced Text Analysis Techniques (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaExperimental NeurologyActa Psychiatrica Scandinavica
- Partner nations
- GermanyCanadaUnited States
In The Last Decade
Shahbaz Syed
27 papers receiving 616 citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 227
- Sociology and Political Science 192
- Health 95
- Cellular and Molecular Neuroscience 90
- Communication 86
Countries citing papers authored by Shahbaz Syed
This map shows the geographic impact of Shahbaz Syed'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 Shahbaz Syed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shahbaz Syed more than expected).
Fields of papers citing papers by Shahbaz Syed
This network shows the impact of papers produced by Shahbaz Syed. 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 Shahbaz Syed. The network helps show where Shahbaz Syed may publish in the future.
Co-authorship network of co-authors of Shahbaz Syed
This figure shows the co-authorship network connecting the top 25 collaborators of Shahbaz Syed. A scholar is included among the top collaborators of Shahbaz Syed 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 Shahbaz Syed. Shahbaz Syed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 3 | |
| 9 | 11 | |
| 10 | 26 | |
| 11 | 2 | |
| 12 | 22 | |
| 13 | The Twitter pandemic: The critical role of Twitter in the dissemination of medical information and misinformation during the COVID-19 pandemicbreakdown → | 249 |
| 14 | 8 | |
| 15 | 48 | |
| 16 | 5 | |
| 17 | 26 | |
| 18 | 58 | |
| 19 | 4 | |
| 20 | 111 |
About Shahbaz Syed
Shahbaz Syed is a scholar working on Artificial Intelligence, Health and Family Practice, having authored 30 papers that have together received 640 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (11 papers) and Advanced Text Analysis Techniques (8 papers). The work is most often cited by research in Communication (86 citations), Health (95 citations) and Artificial Intelligence (227 citations). Shahbaz Syed has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Hans Rosenberg, Salim Rezaie, Benno Stein, Martin Potthast, Henning Wachsmuth, Michael Völske, Stephen W.P. Kemp, Aubrey A. Webb, Sarah K. Walsh and Rajiv Midha. Their work appears in journals such as SHILAP Revista de lepidopterología, Experimental Neurology and Acta Psychiatrica Scandinavica.
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.