Nathan Good
- Sociology and Political Science top 10%
- Information Systems top 5%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Computer Networks and Communications
- Co-authors
- Ira RubinsteinChris Jay HoofnagleAshkan SoltaniDavid WagnerSerge EgelmanPrimal WijesekeraJoel ReardonIrwin Reyes
- Topics
- Privacy, Security, and Data Protection (7 papers)Advanced Malware Detection Techniques (5 papers)User Authentication and Security Systems (2 papers)
- Journals
- TrialsSymposium On Usable Privacy and SecurityScholarWorks@UMassAmherst (University of Massachusetts Amherst)
- Partner nations
- United StatesCanadaSwitzerland
In The Last Decade
Nathan Good
11 papers receiving 240 citations
Peers
Comparison fields: 5 of 45
- Sociology and Political Science 169
- Information Systems 117
- Artificial Intelligence 93
- Signal Processing 68
- Computer Networks and Communications 22
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-authorship network of co-authors of Nathan Good
This figure shows the co-authorship network connecting the top 25 collaborators of Nathan Good. A scholar is included among the top collaborators of Nathan Good 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 Nathan Good. Nathan Good is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 1 | |
| 3 | 45 | |
| 4 | Turtle Guard: Helping Android Users Apply Contextual Privacy Preferences | 25 |
| 5 | Behavioral Advertising: The Offer You Cannot Refuse | 20 |
| 6 | 7 | |
| 7 | 51 | |
| 8 | 88 | |
| 9 | Regular Expression Recipes for Windows Developers: A Problem-Solution Approach (A Problem-Solution Approach) | 1 |
| 10 | 1 | |
| 11 | 4 |
About Nathan Good
Nathan Good is a scholar working on Signal Processing, Software and Law, having authored 11 papers that have together received 256 indexed citations. Recurring topics across this work include Privacy, Security, and Data Protection (7 papers), Advanced Malware Detection Techniques (5 papers) and User Authentication and Security Systems (2 papers). The work is most often cited by research in Signal Processing (68 citations), Information Systems (117 citations) and Sociology and Political Science (169 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, David Wagner, Serge Egelman, Primal Wijesekera, Joel Reardon, Irwin Reyes, Konstantin Beznosov and Khaled El Emam. Their work appears in journals such as Trials, Symposium On Usable Privacy and Security and ScholarWorks@UMassAmherst (University of Massachusetts Amherst).
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.