Parang Saraf
Impact in
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
-
- Social Media and Politics
Papers in
-
- Complex Network Analysis Techniques 5
- Opinion Dynamics and Social Influence 4
-
- Advanced Text Analysis Techniques 2
- Bayesian Modeling and Causal Inference 1
- Co-authors
- Naren Ramakrishnan (11 shared papers)Fang Jin (2 shared papers)Yang Cao (1 shared paper)Edward J. Dougherty (1 shared paper)Nathan Self (7 shared papers)P. J. Butler (3 shared papers)Wei Wang (1 shared paper)Scotland Leman (1 shared paper)
- Journals
- PLoS ONE (1 paper)Technometrics (1 paper)Social Network Analysis and Mining (1 paper)2018 Winter Simulation Conference (WSC) (1 paper)
- Partner nations
- United StatesEcuadorPuerto Rico
In The Last Decade
Parang Saraf
11 papers receiving 295 citations
Peers
Comparison fields: 5 of 45
- Statistical and Nonlinear Physics 153
- Communication 32
- Information Systems 89
- Management Science and Operations Research 44
- Sociology and Political Science 145
Countries citing papers authored by Parang Saraf
This map shows the geographic impact of Parang Saraf'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 Parang Saraf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Parang Saraf more than expected).
Fields of papers citing papers by Parang Saraf
This network shows the impact of papers produced by Parang Saraf. 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 Parang Saraf. The network helps show where Parang Saraf may publish in the future.
Co-authors
The 25 scholars most cited alongside Parang Saraf, 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 | 2013 | 205 | |
| 2 | 2013 | 33 | |
| 3 | 2016 | 17 | |
| 4 | 2020 | 13 | |
| 5 | 2016 | 12 | |
| 6 | 2015 | 9 | |
| 7 | 2019 | 5 | |
| 8 | 2018 | 3 | |
| 9 | 2019 | 3 | |
| 10 | 2020 | 2 | |
| 11 | 2014 | 1 |
About Parang Saraf
Parang Saraf is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Sociology and Political Science, Computer Vision and Pattern Recognition and Epidemiology, having authored 11 papers that have together received 303 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Opinion Dynamics and Social Influence (4 papers), Data Visualization and Analytics (3 papers), Data-Driven Disease Surveillance (2 papers), Misinformation and Its Impacts (2 papers), Advanced Text Analysis Techniques (2 papers), Big Data and Business Intelligence (1 paper) and Bayesian Modeling and Causal Inference (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (153 citations), Communication (32 citations), Information Systems (89 citations), Management Science and Operations Research (44 citations) and Sociology and Political Science (145 citations). Parang Saraf has collaborated with scholars based in United States, Ecuador and Puerto Rico. Frequent co-authors include Naren Ramakrishnan, Fang Jin, Yang Cao, Edward J. Dougherty, Nathan Self, P. J. Butler, Wei Wang, Scotland Leman, Andrew Hoegh and Abhijin Adiga. Their work appears in journals such as PLoS ONE, Technometrics, Social Network Analysis and Mining and 2018 Winter Simulation Conference (WSC).
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.