Evgeny Kotelnikov
- Artificial Intelligence top 1%
- Information Systems top 5%
- Sociology and Political Science
- Social Psychology
- Management Science and Operations Research
- Co-authors
- Natalia LoukachevitchSuresh ManandharYanyan ZhaoIon AndroutsopoulosMahmoud Al‐AyyoubSalud María Jiménez-ZafraMaria PontikiHaris Papageorgiou
- Topics
- Sentiment Analysis and Opinion Mining (16 papers)Topic Modeling (14 papers)Advanced Text Analysis Techniques (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessJournal of Physics Conference Series
In The Last Decade
Evgeny Kotelnikov
22 papers receiving 885 citations
Hit Papers
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 905
- Information Systems 109
- Sociology and Political Science 69
- Social Psychology 25
- Management Science and Operations Research 21
Countries citing papers authored by Evgeny Kotelnikov
This map shows the geographic impact of Evgeny Kotelnikov'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 Evgeny Kotelnikov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evgeny Kotelnikov more than expected).
Fields of papers citing papers by Evgeny Kotelnikov
This network shows the impact of papers produced by Evgeny Kotelnikov. 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 Evgeny Kotelnikov. The network helps show where Evgeny Kotelnikov may publish in the future.
Co-authorship network of co-authors of Evgeny Kotelnikov
This figure shows the co-authorship network connecting the top 25 collaborators of Evgeny Kotelnikov. A scholar is included among the top collaborators of Evgeny Kotelnikov 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 Evgeny Kotelnikov. Evgeny Kotelnikov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 9 | |
| 10 | 4 | |
| 11 | 12 | |
| 12 | 12 | |
| 13 | 1 | |
| 14 | 3 | |
| 15 | Stance Detection in Russian: a Feature Selection and Machine Learning Based Approach. | 5 |
| 16 | 2 | |
| 17 | SemEval-2016 Task 5: Aspect Based Sentiment Analysisbreakdown → | 799 |
| 18 | 17 | |
| 19 | Semantic similarity for aspect-based sentiment analysis. | 8 |
| 20 | SentiRuEval: testing object-oriented sentiment analysis systems in Russian | 28 |
About Evgeny Kotelnikov
Evgeny Kotelnikov is a scholar working on Artificial Intelligence, Information Systems and General Social Sciences, having authored 24 papers that have together received 941 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (16 papers), Topic Modeling (14 papers) and Advanced Text Analysis Techniques (14 papers). The work is most often cited by research in Artificial Intelligence (905 citations), General Social Sciences (21 citations) and Information Systems (109 citations). Evgeny Kotelnikov has collaborated with scholars based in Russia, Türkiye and Jordan. Frequent co-authors include Natalia Loukachevitch, Suresh Manandhar, Yanyan Zhao, Ion Androutsopoulos, Mahmoud Al‐Ayyoub, Salud María Jiménez-Zafra, Maria Pontiki, Haris Papageorgiou, Xavier Tannier and Gülşen Eryiğit. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Journal of Physics Conference Series.
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.