Marián Šimko

699 citations
27 papers · 294 indexed · h-index 10

Marián Šimko

24 papers receiving 274 citations

Peers

Marián Šimko
Comparison fields: 5 of 67
  • Computer Science Applications 52
  • Artificial Intelligence 204
  • Information Systems 76
  • Communication 19
  • Developmental and Educational Psychology 15
Replace Ghassan Z. Qadah with:
Ghassan Z. Qadah United Arab Emirates
Youness Madani Morocco
Arif Nurwidyantoro Australia
Sambhav Gupta India
Giovanni Moretti Italy
Hongfei Lin China
Slavko Žitnik Slovenia
Zhen Yue United States
Alexandra Vtyurina Canada
Hossein Fani Canada
Marián Šimko relative to Ghassan Z. Qadah United Arab Emirates Ghassan Z. Qadah's profile →
Citations per field
00.5×10×14.7×
Ghassan Z. Qadah · 1×
Citations per year

Countries citing papers authored by Marián Šimko

Since Specialization
Citations

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

Fields of papers citing papers by Marián Šimko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 12 scholars most cited alongside Marián Šimko, 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 Marián Šimko Line = papers co-authored together Marián Šimko links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20242
4 20237
5 20221
6 20221
7 202126
8 202042
9 20202
10 201812
11 20186
12 20185
13
Blog Style Classification: Refining Affective Blogs
20161
14 201611
15 20125
16
Lightweight semantics for the "wild Web"
20112
17
Supporting Collaborative Web-based Education via Annotations
20118
18 201043
19
Automatic Concept Relationships Discovery for an Adaptive E-course
200918
20 200126

About Marián Šimko

Marián Šimko is a scholar working on Artificial Intelligence, Computer Science Applications, Information Systems, Transportation and Computer Networks and Communications, having authored 27 papers that have together received 294 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (8 papers), Sentiment Analysis and Opinion Mining (7 papers), Advanced Text Analysis Techniques (7 papers), Semantic Web and Ontologies (5 papers), Intelligent Tutoring Systems and Adaptive Learning (3 papers), Open Education and E-Learning (3 papers) and Spam and Phishing Detection (2 papers). The work is most often cited by research in Computer Science Applications (52 citations), Artificial Intelligence (204 citations), Information Systems (76 citations), Communication (19 citations) and Developmental and Educational Psychology (15 citations). Marián Šimko has collaborated with scholars based in Slovakia, United States and Germany. Frequent co-authors include Mária Bieliková, Michal Barla, Ethan Taub, Regula Markwalder, Markus Wenger, Róbert Móro, Marcel Martončik, Matúš Adamkovič, Ivan Srba and Johan Van Goethem. Their work appears in journals such as Computers & Education, IEEE Transactions on Learning Technologies, Complex & Intelligent Systems, World Wide Web and Expert Systems with Applications.

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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2026