Matthew S. Gerber
- Artificial Intelligence top 2%
- Sociology and Political Science top 5%
- Information Systems top 5%
- Transportation top 5%
- Applied Psychology top 5%
- Co-authors
- Laura E. BarnesDonald E. BrownJoyce ChaiKiana Jafari MeimandiKamran KowsariMojtaba HeidarysafaYu HuangHaoyi Xiong
- Topics
- Digital Mental Health Interventions (11 papers)Topic Modeling (9 papers)Crime Patterns and Interventions (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaEuropean Journal of Operational ResearchIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- United StatesIranAustria
In The Last Decade
Matthew S. Gerber
47 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Artificial Intelligence 654
- Sociology and Political Science 427
- Information Systems 243
- Transportation 159
- Applied Psychology 137
Countries citing papers authored by Matthew S. Gerber
This map shows the geographic impact of Matthew S. Gerber'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 Matthew S. Gerber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew S. Gerber more than expected).
Fields of papers citing papers by Matthew S. Gerber
This network shows the impact of papers produced by Matthew S. Gerber. 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 Matthew S. Gerber. The network helps show where Matthew S. Gerber may publish in the future.
Co-authorship network of co-authors of Matthew S. Gerber
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew S. Gerber. A scholar is included among the top collaborators of Matthew S. Gerber 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 Matthew S. Gerber. Matthew S. Gerber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 32 | |
| 2 | 20 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 8 | |
| 7 | 41 | |
| 8 | 7 | |
| 9 | 19 | |
| 10 | 3 | |
| 11 | 7 | |
| 12 | 9 | |
| 13 | 29 | |
| 14 | 20 | |
| 15 | 26 | |
| 16 | 50 | |
| 17 | 56 | |
| 18 | A Joint Model of Implicit Arguments for Nominal Predicates | 2 |
| 19 | Beyond NomBank: A Study of Implicit Arguments for Nominal Predicates | 74 |
| 20 | Open-domain Commonsense Reasoning Using Discourse Relations from a Corpus of Weblog Stories | 6 |
About Matthew S. Gerber
Matthew S. Gerber is a scholar working on Applied Psychology, Transportation and Health Informatics, having authored 49 papers that have together received 1.5k indexed citations. Recurring topics across this work include Digital Mental Health Interventions (11 papers), Topic Modeling (9 papers) and Crime Patterns and Interventions (7 papers). The work is most often cited by research in Applied Psychology (137 citations), Transportation (159 citations) and Artificial Intelligence (654 citations). Matthew S. Gerber has collaborated with scholars based in United States, Iran and Austria. Frequent co-authors include Laura E. Barnes, Donald E. Brown, Joyce Chai, Kiana Jafari Meimandi, Kamran Kowsari, Mojtaba Heidarysafa, Yu Huang, Haoyi Xiong, Xiaofeng Wang and Philip I. Chow. Their work appears in journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and IEEE Transactions on Intelligent Transportation Systems.
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.