Faranak Abri
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
- Information Systems top 10%
- Spam and Phishing Detection
- Information and Cyber Security
Papers in
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- Sentiment Analysis and Opinion Mining 5
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- Spam and Phishing Detection 9
- Information and Cyber Security 5
- Co-authors
- Akbar Siami Namin (21 shared papers)Sima Siami‐Namini (4 shared papers)Keith S. Jones (12 shared papers)David R. W. Sears (3 shared papers)Miriam Armstrong (1 shared paper)Huyen N. Nguyen (1 shared paper)Vung Pham (1 shared paper)Tommy Dang (1 shared paper)
- Journals
- IEEE Access (5 papers)Electronics (1 paper)Journal of Advances in Information Technology (1 paper)2021 IEEE International Conference on Big Data (Big Data) (1 paper)2022 IEEE International Conference on Big Data (Big Data) (2 papers)
- Partner nations
- United StatesNigeriaHungary
In The Last Decade
Faranak Abri
22 papers receiving 175 citations
Peers
Comparison fields: 5 of 52
- Signal Processing 50
- Information Systems 75
- Artificial Intelligence 78
- Computer Networks and Communications 49
- Health Informatics 1
Countries citing papers authored by Faranak Abri
This map shows the geographic impact of Faranak Abri'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 Faranak Abri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faranak Abri more than expected).
Fields of papers citing papers by Faranak Abri
This network shows the impact of papers produced by Faranak Abri. 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 Faranak Abri. The network helps show where Faranak Abri may publish in the future.
Co-authors
The 9 scholars most cited alongside Faranak Abri, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 40 | |
| 2 | 2019 | 38 | |
| 3 | 2020 | 19 | |
| 4 | 2020 | 10 | |
| 5 | 2020 | 9 | |
| 6 | 2023 | 7 | |
| 7 | 2022 | 6 | |
| 8 | 2021 | 6 | |
| 9 | 2022 | 6 | |
| 10 | 2022 | 5 | |
| 11 | 2023 | 5 | |
| 12 | 2024 | 3 | |
| 13 | 2024 | 3 | |
| 14 | 2020 | 3 | |
| 15 | 2022 | 3 | |
| 16 | 2024 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2022 | 2 | |
| 19 | 2020 | 2 | |
| 20 | 2023 | 2 |
About Faranak Abri
Faranak Abri is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Computer Networks and Communications and Sociology and Political Science, having authored 24 papers that have together received 176 indexed citations. Recurring topics across this work include Spam and Phishing Detection (9 papers), Advanced Malware Detection Techniques (6 papers), Network Security and Intrusion Detection (5 papers), Sentiment Analysis and Opinion Mining (5 papers), Misinformation and Its Impacts (5 papers), Information and Cyber Security (5 papers), Time Series Analysis and Forecasting (3 papers) and Multisensory perception and integration (2 papers). The work is most often cited by research in Signal Processing (50 citations), Information Systems (75 citations), Artificial Intelligence (78 citations), Computer Networks and Communications (49 citations) and Health Informatics (1 citation). Faranak Abri has collaborated with scholars based in United States, Nigeria and Hungary. Frequent co-authors include Akbar Siami Namin, Sima Siami‐Namini, Keith S. Jones, David R. W. Sears, Miriam Armstrong, Huyen N. Nguyen, Vung Pham, Tommy Dang and Tien Thanh Nguyen. Their work appears in journals such as IEEE Access, Electronics, Journal of Advances in Information Technology, 2021 IEEE International Conference on Big Data (Big Data) and 2022 IEEE International Conference on Big Data (Big Data).
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.