Güneş Acar
- Artificial Intelligence top 2%
- Information Systems top 1%
- Sociology and Political Science top 5%
- Signal Processing top 2%
- Computer Networks and Communications top 5%
- Co-authors
- Claudia DíazMarc JuárezArvind NarayananSteven EnglehardtRachel GreenstadtSadia AfrozArunesh MathurMichael Jan Friedman
- Topics
- Internet Traffic Analysis and Secure E-voting (13 papers)Privacy, Security, and Data Protection (10 papers)Spam and Phishing Detection (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaElectronic Commerce Research and ApplicationsProceedings of the ACM on Human-Computer Interaction
- Partner nations
- BelgiumUnited StatesNetherlands
In The Last Decade
Güneş Acar
22 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 663
- Information Systems 465
- Sociology and Political Science 445
- Signal Processing 364
- Computer Networks and Communications 302
Countries citing papers authored by Güneş Acar
This map shows the geographic impact of Güneş Acar'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 Güneş Acar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Güneş Acar more than expected).
Fields of papers citing papers by Güneş Acar
This network shows the impact of papers produced by Güneş Acar. 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 Güneş Acar. The network helps show where Güneş Acar may publish in the future.
Co-authorship network of co-authors of Güneş Acar
This figure shows the co-authorship network connecting the top 25 collaborators of Güneş Acar. A scholar is included among the top collaborators of Güneş Acar 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 Güneş Acar. Güneş Acar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 1 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | Digital monitoring of unlawful dark patterns: What role for public interest technology? | 1 |
| 8 | IoT Inspector | 17 |
| 9 | 16 | |
| 10 | 77 | |
| 11 | 31 | |
| 12 | Dark Patterns at Scalebreakdown → | 252 |
| 13 | 36 | |
| 14 | 34 | |
| 15 | 27 | |
| 16 | The leaking battery A privacy analysis of the HTML5 Battery Status API | 15 |
| 17 | 203 | |
| 18 | The Web Never Forgetsbreakdown → | 250 |
| 19 | 9 | |
| 20 | 144 |
About Güneş Acar
Güneş Acar is a scholar working on Signal Processing, General Decision Sciences and Information Systems, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (13 papers), Privacy, Security, and Data Protection (10 papers) and Spam and Phishing Detection (9 papers). The work is most often cited by research in Signal Processing (364 citations), Information Systems (465 citations) and Artificial Intelligence (663 citations). Güneş Acar has collaborated with scholars based in Belgium, United States and Netherlands. Frequent co-authors include Claudia Díaz, Marc Juárez, Arvind Narayanan, Steven Englehardt, Rachel Greenstadt, Sadia Afroz, Arunesh Mathur, Michael Jan Friedman, Jonathan Mayer and Marshini Chetty. Their work appears in journals such as SHILAP Revista de lepidopterología, Electronic Commerce Research and Applications and Proceedings of the ACM on Human-Computer Interaction.
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.