Serkan Erbis

7 papers receiving 385 citations

Hit Papers

Novel keyword co-occurrence network-based methods to fost...2017202620202023201750100150200250

Peers

Serkan Erbis
Comparison fields: 5 of 135
  • Mechanical Engineering 77
  • Industrial and Manufacturing Engineering 55
  • Electrical and Electronic Engineering 42
  • Artificial Intelligence 41
  • Strategy and Management 39
Replace Nwakamma Ninduwezuor -Ehiobu with:
Nwakamma Ninduwezuor -Ehiobu Nigeria
Jonas Flodén Sweden
Stefan N. Groesser Switzerland
Adedayo Adefemi Nigeria
Annibal Parracho Sant’Anna Brazil
Alexander Obaigbena United States
Steven Hoffenson United States
Dorota Klimecka-Tatar Poland
Serkan Erbis relative to Nwakamma Ninduwezuor -Ehiobu Nigeria Nwakamma Ninduwezuor -Ehiobu's profile →
Citations per field
00.5×9.6×
Nwakamma Ninduwezuor -Ehiobu · 1×
Citations per year

Countries citing papers authored by Serkan Erbis

Since Specialization
Citations

This map shows the geographic impact of Serkan Erbis'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 Serkan Erbis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Serkan Erbis more than expected).

Fields of papers citing papers by Serkan Erbis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Serkan Erbis. 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 Serkan Erbis. The network helps show where Serkan Erbis may publish in the future.

Co-authorship network of co-authors of Serkan Erbis

This figure shows the co-authorship network connecting the top 25 collaborators of Serkan Erbis. A scholar is included among the top collaborators of Serkan Erbis 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 Serkan Erbis. Serkan Erbis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1
Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literaturebreakdown →
258
2 28
3 1
4 73
5 14
6 27
7 5

About Serkan Erbis

Serkan Erbis is a scholar working on Industrial and Manufacturing Engineering, Automotive Engineering and Statistics, Probability and Uncertainty, having authored 7 papers that have together received 406 indexed citations. Recurring topics across this work include Extraction and Separation Processes (3 papers), Advanced Battery Technologies Research (2 papers) and Nanoparticles: synthesis and applications (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (55 citations), Statistics, Probability and Uncertainty (27 citations) and Health Informatics (5 citations). Serkan Erbis has collaborated with scholars based in United States and Mexico. Frequent co-authors include John Isaacs, Sagar Kamarthi, Srinivasan Radhakrishnan, Matthew J. Eckelman, Goksin Kavlak, E. M. Harper, Philip Nuss, T. E. Graedel, James C. Benneyan and Leila Pourzahedi. Their work appears in journals such as PLoS ONE, ACS Sustainable Chemistry & Engineering and Risk Analysis.

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.

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