Fabrício Benevenuto
- Sociology and Political Science top 0.5%
- Information Systems top 0.1%
- Artificial Intelligence top 0.5%
- Statistical and Nonlinear Physics top 0.2%
- Communication top 0.2%
- Co-authors
- Meeyoung ChaKrishna P. GummadiHamed HaddadiVirgı́lio AlmeidaJussara M. AlmeidaTiago RodriguesMarcos André GonçalvesMatheus Araújo
- Topics
- Spam and Phishing Detection (54 papers)Misinformation and Its Impacts (50 papers)Social Media and Politics (40 papers)
- Partner nations
- BrazilGermanyUnited States
In The Last Decade
Fabrício Benevenuto
134 papers receiving 6.2k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Sociology and Political Science 2.6k
- Information Systems 2.4k
- Artificial Intelligence 2.3k
- Statistical and Nonlinear Physics 2.2k
- Communication 1.4k
Countries citing papers authored by Fabrício Benevenuto
This map shows the geographic impact of Fabrício Benevenuto'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 Fabrício Benevenuto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrício Benevenuto more than expected).
Fields of papers citing papers by Fabrício Benevenuto
This network shows the impact of papers produced by Fabrício Benevenuto. 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 Fabrício Benevenuto. The network helps show where Fabrício Benevenuto may publish in the future.
Co-authorship network of co-authors of Fabrício Benevenuto
This figure shows the co-authorship network connecting the top 25 collaborators of Fabrício Benevenuto. A scholar is included among the top collaborators of Fabrício Benevenuto 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 Fabrício Benevenuto. Fabrício Benevenuto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 9 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | Detecting Misinformation on WhatsApp without Breaking Encryption. | 2 |
| 13 | 20 | |
| 14 | 8 | |
| 15 | 59 | |
| 16 | 9 | |
| 17 | 0 | |
| 18 | 28 | |
| 19 | Characterization and Analysis of User Profiles in Online Video Sharing Systems | 17 |
| 20 | A Multi-view Approach for Detecting Non-Cooperative Users in Online Video Sharing Systems | 4 |
About Fabrício Benevenuto
Fabrício Benevenuto is a scholar working on Communication, Information Systems and Statistical and Nonlinear Physics, having authored 158 papers that have together received 6.7k indexed citations. Recurring topics across this work include Spam and Phishing Detection (54 papers), Misinformation and Its Impacts (50 papers) and Social Media and Politics (40 papers). The work is most often cited by research in Communication (1.4k citations), Statistical and Nonlinear Physics (2.2k citations) and Information Systems (2.4k citations). Fabrício Benevenuto has collaborated with scholars based in Brazil, Germany and United States. Frequent co-authors include Meeyoung Cha, Krishna P. Gummadi, Hamed Haddadi, Virgı́lio Almeida, Jussara M. Almeida, Tiago Rodrigues, Marcos André Gonçalves, Matheus Araújo, Adriano Veloso and Júlio C. S. Reis. Their work appears in journals such as PLoS ONE, Communications of the ACM and ACM Computing Surveys.
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.