Benjamin Markines
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Information Systems top 2%
- Recommender Systems and Techniques
- Spam and Phishing Detection
Papers in
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- Advanced Graph Neural Networks 4
- Topic Modeling 3
- Advanced Text Analysis Techniques 1
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- Recommender Systems and Techniques 7
- Spam and Phishing Detection 1
- Co-authors
- Filippo Menczer (10 shared papers)Ciro Cattuto (4 shared papers)Rossano Schifanella (2 shared papers)Alain Barrat (2 shared papers)Filippo Radicchi (1 shared paper)Alessandro Vespignani (1 shared paper)Santo Fortunato (1 shared paper)Luca Maria Aiello (1 shared paper)
- Journals
- ACM Transactions on the Web (1 paper)ACM SIGWEB Newsletter (1 paper)arXiv (Cornell University) (1 paper)Physical Review E (1 paper)
- Partner nations
- United StatesItalyFrance
In The Last Decade
Benjamin Markines
12 papers receiving 854 citations
Peers
Comparison fields: 5 of 77
- Statistical and Nonlinear Physics 484
- Information Systems 386
- Statistics, Probability and Uncertainty 84
- Communication 79
- Artificial Intelligence 365
Countries citing papers authored by Benjamin Markines
This map shows the geographic impact of Benjamin Markines'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 Benjamin Markines with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Markines more than expected).
Fields of papers citing papers by Benjamin Markines
This network shows the impact of papers produced by Benjamin Markines. 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 Benjamin Markines. The network helps show where Benjamin Markines may publish in the future.
Co-authors
The 12 scholars most cited alongside Benjamin Markines, 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 | 2012 | 278 | |
| 2 | 2009 | 214 | |
| 3 | 2009 | 166 | |
| 4 | 2009 | 113 | |
| 5 | 2010 | 95 | |
| 6 | 2009 | 15 | |
| 7 | 2008 | 11 | |
| 8 | 2008 | 9 | |
| 9 | 2009 | 5 | |
| 10 | 2009 | 4 | |
| 11 | Socially induced semantic networks and applications | 2009 | 2 |
| 12 | 2009 | 1 |
About Benjamin Markines
Benjamin Markines is a scholar working on Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics, Computer Science Applications and Computer Networks and Communications, having authored 12 papers that have together received 913 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (4 papers), Opinion Dynamics and Social Influence (3 papers), Topic Modeling (3 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Advanced Text Analysis Techniques (1 paper) and Spam and Phishing Detection (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (484 citations), Information Systems (386 citations), Statistics, Probability and Uncertainty (84 citations), Communication (79 citations) and Artificial Intelligence (365 citations). Benjamin Markines has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Filippo Menczer, Ciro Cattuto, Rossano Schifanella, Alain Barrat, Filippo Radicchi, Alessandro Vespignani, Santo Fortunato, Luca Maria Aiello, Gerd Stumme and Andreas Hotho. Their work appears in journals such as ACM Transactions on the Web, ACM SIGWEB Newsletter, arXiv (Cornell University) and Physical Review E.
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.