Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average within
it), or reaches the top citation threshold in at least one of its specific research topics.
2009A systematic analysis of performance measures for classification tasks
Countries citing papers authored by Marina Sokolova
Since Specialization
Citations
This map shows the geographic impact of Marina Sokolova'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 Marina Sokolova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marina Sokolova more than expected).
This network shows the impact of papers produced by Marina Sokolova. 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 Marina Sokolova. The network helps show where Marina Sokolova may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marina Sokolova, linked wherever they have
co-authored with each other. Click a name or a connecting line to browse the papers they
share.
Border = papers with Marina SokolovaLine = papers co-authored togetherMarina Sokolova links everyone, so they are left out of the graph.
Marina Sokolova is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 57 papers that have together received 4.6k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (14 papers), Topic Modeling (13 papers), Advanced Text Analysis Techniques (8 papers), Spam and Phishing Detection (7 papers), Multi-Agent Systems and Negotiation (7 papers), Privacy, Security, and Data Protection (6 papers), Privacy-Preserving Technologies in Data (6 papers) and Text and Document Classification Technologies (5 papers). The work is most often cited by research in Artificial Intelligence (1.9k citations), Health Information Management (157 citations) and Computer Vision and Pattern Recognition (671 citations). Marina Sokolova has collaborated with scholars based in Canada, Moldova and Poland. Frequent co-authors include Guy Lapalme, Stan Matwin, Stan Śzpakowicz, Mario Marchand, Kambiz Ghazinour, David Schramm, Vivi Năstase, Antonio Fernández‐Caballero, José Carlos Castillo and Diana Inkpen.
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.