Ivan Srba

869 citations
35 papers · 424 · h-index 11

Impact in

Papers in

Ivan Srba

31 papers receiving 408 citations

Peers

Ivan Srba
Comparison fields: 5 of 53
  • Computer Science Applications 146
  • Information Systems 229
  • Communication 59
  • Artificial Intelligence 236
  • Developmental and Educational Psychology 58
Replace Bernardo Pereira Nunes with:
Bernardo Pereira Nunes Brazil
Amal Zouaq Canada
Jörg Rech Germany
Felix Ming Fai Wong United States
Behnam Taraghi Austria
Jose Martin Spain
Tobias Hecking Germany
Sergej Zerr Germany
Marc Spaniol Germany
Aneesha Bakharia Australia
Ivan Srba relative to Bernardo Pereira Nunes Brazil Bernardo Pereira Nunes's profile →
Citations per field
00.5×1.5×
Bernardo Pereira Nunes · 1×
Citations per year

Countries citing papers authored by Ivan Srba

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Srba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ivan Srba, 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 Ivan Srba Line = papers co-authored together Ivan Srba links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016101
2 201456
3 201645
4 202126
5 202225
6 201520
7 201918
8 201516
9 201715
10 202314
11 202411
12
Unravelling the basic concepts and intents of misbehavior in post-truth society
20199
13 20248
14 20218
15 20178
16 20227
17 20216
18 20105
19 20234
20 20114

About Ivan Srba

Ivan Srba is a scholar working on Artificial Intelligence, Information Systems, Sociology and Political Science, Computer Science Applications and Developmental and Educational Psychology, having authored 35 papers that have together received 424 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (9 papers), Topic Modeling (9 papers), Expert finding and Q&A systems (8 papers), Mobile Crowdsensing and Crowdsourcing (7 papers), Innovative Teaching and Learning Methods (5 papers), Spam and Phishing Detection (4 papers), Natural Language Processing Techniques (4 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Computer Science Applications (146 citations), Information Systems (229 citations), Communication (59 citations), Artificial Intelligence (236 citations) and Developmental and Educational Psychology (58 citations). Ivan Srba has collaborated with scholars based in Slovakia, Czechia and United Kingdom. Frequent co-authors include Mária Bieliková, Róbert Móro, Jakub Šimko, Joseph Jay Williams, Cesare Pautasso, Peter Babinec, Miloš Savić, Mirjana Ivanović, Marián Šimko and Marcel Martončik. Their work appears in journals such as Complex & Intelligent Systems, IEEE Software, ACM Transactions on Intelligent Systems and Technology, ACM Transactions on the Web and Computers & Education.

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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