Peter Story
Impact in
- Information Systems top 5%
- Digital and Cyber Forensics
- Spam and Phishing Detection
- Sociology and Political Science top 10%
- Privacy, Security, and Data Protection
Papers in
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- Privacy, Security, and Data Protection 9
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- Privacy-Preserving Technologies in Data 3
- Hate Speech and Cyberbullying Detection 2
- Internet Traffic Analysis and Secure E-voting 2
- Co-authors
- Norman Sadeh (8 shared papers)Daniel Smullen (5 shared papers)Sebastian Zimmeck (3 shared papers)N. Cameron Russell (2 shared papers)Joël R. Reidenberg (2 shared papers)Florian Schaub (6 shared papers)Shomir Wilson (4 shared papers)Ziqi Wang (1 shared paper)
- Journals
- Journal of Clinical Pathology (1 paper)ACM Transactions on the Web (1 paper)Semantic Web (1 paper)SHILAP Revista de lepidopterología (2 papers)Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (1 paper)
- Partner nations
- United States
In The Last Decade
Peter Story
9 papers receiving 327 citations
Peers
Comparison fields: 5 of 66
- Information Systems 135
- Sociology and Political Science 234
- Signal Processing 55
- Artificial Intelligence 159
- Human-Computer Interaction 15
Countries citing papers authored by Peter Story
This map shows the geographic impact of Peter Story'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 Peter Story with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Story more than expected).
Fields of papers citing papers by Peter Story
This network shows the impact of papers produced by Peter Story. 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 Peter Story. The network helps show where Peter Story may publish in the future.
Co-authors
The 24 scholars most cited alongside Peter Story, 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 | 2019 | 105 | |
| 2 | 2017 | 53 | |
| 3 | 2020 | 43 | |
| 4 | 1985 | 37 | |
| 5 | 2018 | 31 | |
| 6 | 2021 | 25 | |
| 7 | 2018 | 22 | |
| 8 | 2021 | 11 | |
| 9 | 2022 | 11 | |
| 10 | 2024 | 0 |
About Peter Story
Peter Story is a scholar working on Sociology and Political Science, Artificial Intelligence, Information Systems, Computer Science Applications and Clinical Psychology, having authored 10 papers that have together received 338 indexed citations. Recurring topics across this work include Privacy, Security, and Data Protection (9 papers), Privacy-Preserving Technologies in Data (3 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Hate Speech and Cyberbullying Detection (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Sexuality, Behavior, and Technology (1 paper), Advanced Malware Detection Techniques (1 paper) and Information and Cyber Security (1 paper). The work is most often cited by research in Information Systems (135 citations), Sociology and Political Science (234 citations), Signal Processing (55 citations), Artificial Intelligence (159 citations) and Human-Computer Interaction (15 citations). Peter Story has collaborated with scholars based in United States. Frequent co-authors include Norman Sadeh, Daniel Smullen, Sebastian Zimmeck, N. Cameron Russell, Joël R. Reidenberg, Florian Schaub, Shomir Wilson, Ziqi Wang, Abhilasha Ravichander and Lorrie Faith Cranor. Their work appears in journals such as Journal of Clinical Pathology, ACM Transactions on the Web, Semantic Web, SHILAP Revista de lepidopterología and Research Showcase @ Carnegie Mellon University (Carnegie Mellon University).
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.