Danesh Irani

805 citations
15 papers · 453 indexed · h-index 12

Impact in

Papers in

Danesh Irani

15 papers receiving 426 citations

Peers

Danesh Irani
Comparison fields: 5 of 37
  • Information Systems 325
  • Artificial Intelligence 263
  • Computer Networks and Communications 167
  • Signal Processing 78
  • Communication 29
Replace Rishabh Kaushal with:
Rishabh Kaushal India
Taejoong Chung United States
Rob Ennals United States
Paul - Alexandru Chirita Germany
Liyun Ru China
Alexander Löser Germany
Shyhtsun Felix Wu United States
Nilesh Bansal Canada
José María Gómez Hidalgo Spain
C. Valliyammai India
Danesh Irani relative to Rishabh Kaushal India Rishabh Kaushal's profile →
Citations per field
00.5×9.6×
Rishabh Kaushal · 1×
Citations per year

Countries citing papers authored by Danesh Irani

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network

The 16 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.

Border = papers with Danesh Irani Line = papers co-authored together Danesh Irani links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 20206
2 20146
3 20145
4 201418
5 201325
6 201349
7 201243
8 201159
9 201151
10 201027
11
Study of Trend-Stuffing on Twitter through Text Classification
201040
12 201011
13 200966
14 200836
15 200711

About Danesh Irani

Danesh Irani is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Transportation, having authored 15 papers that have together received 453 indexed citations. Recurring topics across this work include Spam and Phishing Detection (11 papers), Internet Traffic Analysis and Secure E-voting (5 papers), Web Data Mining and Analysis (4 papers), Misinformation and Its Impacts (3 papers), Text and Document Classification Technologies (3 papers), Network Security and Intrusion Detection (3 papers), Caching and Content Delivery (2 papers) and Peer-to-Peer Network Technologies (1 paper). The work is most often cited by research in Information Systems (325 citations), Artificial Intelligence (263 citations), Computer Networks and Communications (167 citations), Signal Processing (78 citations) and Communication (29 citations). Danesh Irani has collaborated with scholars based in United States and Brazil. Frequent co-authors include Calton Pu, Steve Webb, Wang De, Wang De, Kang Li, De Wang, Kang Li, Kang Li, Jonathon Giffin and Acar Tamersoy. Their work appears in journals such as IEEE Internet Computing, ACM Transactions on Internet Technology, Social Network Analysis and Mining, International Journal of Cooperative Information Systems and Proceedings of the International AAAI Conference on Web and Social Media.

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.

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