Shervin Malmasi
- Artificial Intelligence top 0.5%
- Information Systems top 2%
- Communication top 2%
- Social Psychology top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Marcos ZampieriRitesh KumarMark DrasPreslav NakovAtul Kr. OjhaSara RosenthalNoura FarraOleg Rokhlenko
- Topics
- Natural Language Processing Techniques (51 papers)Topic Modeling (30 papers)Authorship Attribution and Profiling (26 papers)
- Journals
- SHILAP Revista de lepidopterologíaObesityDiabetic Medicine
- Partner nations
- United StatesAustraliaGermany
In The Last Decade
Shervin Malmasi
75 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 2.4k
- Information Systems 299
- Communication 226
- Social Psychology 200
- Computer Vision and Pattern Recognition 143
Countries citing papers authored by Shervin Malmasi
This map shows the geographic impact of Shervin Malmasi'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 Shervin Malmasi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shervin Malmasi more than expected).
Fields of papers citing papers by Shervin Malmasi
This network shows the impact of papers produced by Shervin Malmasi. 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 Shervin Malmasi. The network helps show where Shervin Malmasi may publish in the future.
Co-authorship network of co-authors of Shervin Malmasi
This figure shows the co-authorship network connecting the top 25 collaborators of Shervin Malmasi. A scholar is included among the top collaborators of Shervin Malmasi 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 Shervin Malmasi. Shervin Malmasi 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 34 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 13 | |
| 9 | 56 | |
| 10 | 6 | |
| 11 | 7 | |
| 12 | SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)breakdown → | 447 |
| 13 | 10 | |
| 14 | Findings of the 2019 Conference on Machine Translation (WMT19)breakdown → | 256 |
| 15 | German Dialect Identification Using Classifier Ensembles | 3 |
| 16 | Benchmarking Aggression Identification in Social Media. | 224 |
| 17 | 35 | |
| 18 | 100 | |
| 19 | Subdialectal Differences in Sorani Kurdish | 7 |
| 20 | Norwegian Native Language Identification | 5 |
About Shervin Malmasi
Shervin Malmasi is a scholar working on Artificial Intelligence, Language and Linguistics and Linguistics and Language, having authored 82 papers that have together received 2.6k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (51 papers), Topic Modeling (30 papers) and Authorship Attribution and Profiling (26 papers). The work is most often cited by research in Artificial Intelligence (2.4k citations), Communication (226 citations) and Linguistics and Language (83 citations). Shervin Malmasi has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Marcos Zampieri, Ritesh Kumar, Mark Dras, Preslav Nakov, Atul Kr. Ojha, Sara Rosenthal, Noura Farra, Oleg Rokhlenko, Anjie Fang and Besnik Fetahu. Their work appears in journals such as SHILAP Revista de lepidopterología, Obesity and Diabetic Medicine.
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.