Kyle Shaffer
Impact in
- Information Systems top 5%
- Spam and Phishing Detection
-
- Misinformation and Its Impacts
Papers in
-
- Topic Modeling 4
- Advanced Text Analysis Techniques 2
- Sentiment Analysis and Opinion Mining 2
- Natural Language Processing Techniques 2
- Authorship Attribution and Profiling 1
- Hate Speech and Cyberbullying Detection 1
-
- Complex Network Analysis Techniques 2
- Co-authors
- Nathan O. Hodas (3 shared papers)Svitlana Volkova (3 shared papers)Jin Yea Jang (1 shared paper)Lawrence Phillips (2 shared papers)Jaime Arguello (1 shared paper)Dustin Arendt (1 shared paper)Melissa Roemmele (1 shared paper)Steve DeNeefe (1 shared paper)
- Journals
- arXiv (Cornell University) (1 paper)Proceedings of the International AAAI Conference on Web and Social Media (1 paper)
- Partner nations
- United States
In The Last Decade
Kyle Shaffer
6 papers receiving 294 citations
Peers
Comparison fields: 5 of 44
- Information Systems 168
- Sociology and Political Science 247
- Artificial Intelligence 172
- Communication 29
- Signal Processing 43
Countries citing papers authored by Kyle Shaffer
This map shows the geographic impact of Kyle Shaffer'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 Kyle Shaffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle Shaffer more than expected).
Fields of papers citing papers by Kyle Shaffer
This network shows the impact of papers produced by Kyle Shaffer. 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 Kyle Shaffer. The network helps show where Kyle Shaffer may publish in the future.
Co-authors
The 9 scholars most cited alongside Kyle Shaffer, 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 | 2017 | 258 | |
| 2 | 2017 | 27 | |
| 3 | 2021 | 8 | |
| 4 | 2017 | 6 | |
| 5 | 2021 | 6 | |
| 6 | 2023 | 1 |
About Kyle Shaffer
Kyle Shaffer is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Information Systems and Sociology and Political Science, having authored 6 papers that have together received 306 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Complex Network Analysis Techniques (2 papers), Advanced Text Analysis Techniques (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Natural Language Processing Techniques (2 papers), Software Engineering Research (1 paper), Authorship Attribution and Profiling (1 paper) and Hate Speech and Cyberbullying Detection (1 paper). The work is most often cited by research in Information Systems (168 citations), Sociology and Political Science (247 citations), Artificial Intelligence (172 citations), Communication (29 citations) and Signal Processing (43 citations). Kyle Shaffer has collaborated with scholars based in United States. Frequent co-authors include Nathan O. Hodas, Svitlana Volkova, Jin Yea Jang, Lawrence Phillips, Jaime Arguello, Dustin Arendt, Melissa Roemmele, Steve DeNeefe and Yiyi Wang. Their work appears in journals such as arXiv (Cornell University) 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.