Danesh Irani
Impact in
- Information Systems top 2%
- Spam and Phishing Detection
- User Authentication and Security Systems
- Information and Cyber Security
- Signal Processing top 5%
- Advanced Malware Detection Techniques
Papers in
-
- Spam and Phishing Detection 12
- Web Data Mining and Analysis 4
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- Internet Traffic Analysis and Secure E-voting 6
- Text and Document Classification Technologies 3
- Anomaly Detection Techniques and Applications 2
- Co-authors
- Calton Pu (16 shared papers)Steve Webb (6 shared papers)Wang De (2 shared papers)Wang De (4 shared papers)Engin Kirda (1 shared paper)Davide Balzarotti (1 shared paper)Marco Balduzzi (1 shared paper)Kang Li (1 shared paper)
- Journals
- International Journal of Cooperative Information Systems (1 paper)ACM Transactions on Internet Technology (1 paper)Social Network Analysis and Mining (1 paper)IEEE Internet Computing (1 paper)Lecture notes in computer science (2 papers)
- Partner nations
- United StatesBrazilFrance
In The Last Decade
Danesh Irani
17 papers receiving 598 citations
Peers
Comparison fields: 5 of 43
- Information Systems 480
- Signal Processing 137
- Computer Networks and Communications 236
- Artificial Intelligence 334
- Communication 37
Countries citing papers authored by Danesh Irani
This map shows the geographic impact of Danesh Irani'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 Danesh Irani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danesh Irani more than expected).
Fields of papers citing papers by Danesh Irani
This network shows the impact of papers produced by Danesh Irani. 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 Danesh Irani. The network helps show where Danesh Irani may publish in the future.
Co-authors
The 21 scholars most cited alongside Danesh Irani, 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 | 2011 | 113 | |
| 2 | 2009 | 79 | |
| 3 | 2011 | 74 | |
| 4 | 2011 | 62 | |
| 5 | 2013 | 55 | |
| 6 | Study of Trend-Stuffing on Twitter through Text Classification | 2010 | 45 |
| 7 | 2012 | 44 | |
| 8 | 2008 | 42 | |
| 9 | 2013 | 33 | |
| 10 | 2010 | 32 | |
| 11 | 2014 | 19 | |
| 12 | 2010 | 16 | |
| 13 | 2007 | 12 | |
| 14 | 2014 | 7 | |
| 15 | 2020 | 6 | |
| 16 | 2014 | 6 | |
| 17 | 2010 | 1 |
About Danesh Irani
Danesh Irani is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Sociology and Political Science and Signal Processing, having authored 17 papers that have together received 646 indexed citations. Recurring topics across this work include Spam and Phishing Detection (12 papers), Internet Traffic Analysis and Secure E-voting (6 papers), Network Security and Intrusion Detection (5 papers), Web Data Mining and Analysis (4 papers), Misinformation and Its Impacts (3 papers), Text and Document Classification Technologies (3 papers), Anomaly Detection Techniques and Applications (2 papers) and Caching and Content Delivery (2 papers). The work is most often cited by research in Information Systems (480 citations), Signal Processing (137 citations), Computer Networks and Communications (236 citations), Artificial Intelligence (334 citations) and Communication (37 citations). Danesh Irani has collaborated with scholars based in United States, Brazil and France. Frequent co-authors include Calton Pu, Steve Webb, Wang De, Wang De, Engin Kirda, Davide Balzarotti, Marco Balduzzi, Kang Li, Kang Li and De Wang. Their work appears in journals such as International Journal of Cooperative Information Systems, ACM Transactions on Internet Technology, Social Network Analysis and Mining, IEEE Internet Computing and Lecture notes in 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.