Nathan Good
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
- Information Systems top 5%
- Spam and Phishing Detection
- User Authentication and Security Systems
- Web Data Mining and Analysis
Papers in
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- Privacy, Security, and Data Protection 7
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- Advanced Malware Detection Techniques 5
- Co-authors
- Ira Rubinstein (2 shared papers)Chris Jay Hoofnagle (3 shared papers)Ashkan Soltani (2 shared papers)Joel Reardon (2 shared papers)David Wagner (2 shared papers)Serge Egelman (2 shared papers)Irwin Reyes (2 shared papers)Primal Wijesekera (2 shared papers)
- Journals
- Trials (1 paper)eScholarship (California Digital Library) (1 paper)ScholarWorks@UMassAmherst (University of Massachusetts Amherst) (1 paper)SSRN Electronic Journal (5 papers)Apress eBooks (3 papers)
- Partner nations
- United StatesCanadaSwitzerland
In The Last Decade
Nathan Good
12 papers receiving 285 citations
Peers
Comparison fields: 5 of 46
- Signal Processing 78
- Information Systems 138
- Sociology and Political Science 197
- Artificial Intelligence 106
- Human-Computer Interaction 17
Countries citing papers authored by Nathan Good
This map shows the geographic impact of Nathan Good'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 Nathan Good with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Good more than expected).
Fields of papers citing papers by Nathan Good
This network shows the impact of papers produced by Nathan Good. 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 Nathan Good. The network helps show where Nathan Good may publish in the future.
Co-authors
The 16 scholars most cited alongside Nathan Good, 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 | 105 | |
| 2 | 2012 | 63 | |
| 3 | 2018 | 50 | |
| 4 | Turtle Guard: Helping Android Users Apply Contextual Privacy Preferences | 2017 | 30 |
| 5 | Behavioral Advertising: The Offer You Cannot Refuse | 2012 | 23 |
| 6 | 2020 | 14 | |
| 7 | 2004 | 10 | |
| 8 | 2012 | 8 | |
| 9 | Regular Expression Recipes for Windows Developers: A Problem-Solution Approach (A Problem-Solution Approach) | 2005 | 1 |
| 10 | 2005 | 1 | |
| 11 | 2005 | 1 | |
| 12 | 2019 | 1 | |
| 13 | Regular Expression Recipes: A Problem-Solution Approach | 2004 | 0 |
About Nathan Good
Nathan Good is a scholar working on Sociology and Political Science, Signal Processing, Information Systems, Artificial Intelligence and Law, having authored 13 papers that have together received 307 indexed citations. Recurring topics across this work include Privacy, Security, and Data Protection (7 papers), Advanced Malware Detection Techniques (5 papers), User Authentication and Security Systems (2 papers), RFID technology advancements (1 paper), Hate Speech and Cyberbullying Detection (1 paper), Freedom of Expression and Defamation (1 paper), Internet Traffic Analysis and Secure E-voting (1 paper) and Parallel Computing and Optimization Techniques (1 paper). The work is most often cited by research in Signal Processing (78 citations), Information Systems (138 citations), Sociology and Political Science (197 citations), Artificial Intelligence (106 citations) and Human-Computer Interaction (17 citations). Nathan Good has collaborated with scholars based in United States, Canada and Switzerland. Frequent co-authors include Ira Rubinstein, Chris Jay Hoofnagle, Ashkan Soltani, Joel Reardon, David Wagner, Serge Egelman, Irwin Reyes, Primal Wijesekera, Konstantin Beznosov and Christian Probst. Their work appears in journals such as Trials, eScholarship (California Digital Library), ScholarWorks@UMassAmherst (University of Massachusetts Amherst), SSRN Electronic Journal and Apress eBooks.
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.