Ivan Srba

869 total citations
35 papers, 424 citations indexed

About

Ivan Srba is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Ivan Srba has authored 35 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 15 papers in Information Systems and 10 papers in Sociology and Political Science. Recurrent topics in Ivan Srba's work include Misinformation and Its Impacts (9 papers), Topic Modeling (9 papers) and Expert finding and Q&A systems (8 papers). Ivan Srba is often cited by papers focused on Misinformation and Its Impacts (9 papers), Topic Modeling (9 papers) and Expert finding and Q&A systems (8 papers). Ivan Srba collaborates with scholars based in Slovakia, Czechia and United Kingdom. Ivan Srba's co-authors include Mária Bieliková, Róbert Móro, Jakub Šimko, Joseph Jay Williams, Cesare Pautasso, Peter Babinec, Miloš Savić, Mirjana Ivanović, Marián Šimko and Michal Kompan and has published in prestigious journals such as PLoS ONE, Computers & Education and ACM Computing Surveys.

In The Last Decade

Ivan Srba

31 papers receiving 408 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ivan Srba Slovakia 11 236 229 146 84 59 35 424
Bernardo Pereira Nunes Brazil 10 352 1.5× 181 0.8× 216 1.5× 33 0.4× 39 0.7× 74 524
Amal Zouaq Canada 13 359 1.5× 153 0.7× 210 1.4× 35 0.4× 30 0.5× 48 605
Michelle Bachler United Kingdom 10 89 0.4× 128 0.6× 75 0.5× 39 0.5× 26 0.4× 22 307
Behnam Taraghi Austria 10 69 0.3× 151 0.7× 111 0.8× 39 0.5× 36 0.6× 36 381
Sergej Zerr Germany 10 240 1.0× 130 0.6× 83 0.6× 60 0.7× 22 0.4× 27 396
Jose Martin Spain 3 323 1.4× 110 0.5× 82 0.6× 73 0.9× 18 0.3× 4 422
Qintai Hu China 8 138 0.6× 140 0.6× 122 0.8× 29 0.3× 10 0.2× 11 307
Fotis Lazarinis Greece 14 110 0.5× 173 0.8× 139 1.0× 58 0.7× 15 0.3× 52 429
Jörg Rech Germany 10 101 0.4× 230 1.0× 77 0.5× 27 0.3× 78 1.3× 29 359
Felix Ming Fai Wong United States 9 153 0.6× 74 0.3× 187 1.3× 69 0.8× 55 0.9× 13 394

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-authorship network of co-authors of Ivan Srba

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

All Works

20 of 20 papers shown
1.
2.
Srba, Ivan, Olesya Razuvayevskaya, Róbert Móro, et al.. (2025). A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Models. ACM Transactions on Intelligent Systems and Technology. 17(2). 1–80.
3.
Srba, Ivan, et al.. (2024). On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices. Zenodo (CERN European Organization for Nuclear Research). 522–556. 1 indexed citations
4.
Šimko, Jakub, et al.. (2024). Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation. Zenodo (CERN European Organization for Nuclear Research). 11005–11044. 1 indexed citations
5.
Móro, Róbert, et al.. (2024). Authorship Obfuscation in Multilingual Machine-Generated Text Detection. Zenodo (CERN European Organization for Nuclear Research). 6348–6368. 3 indexed citations
6.
Srba, Ivan, et al.. (2024). A Survey on Stability of Learning with Limited Labelled Data and its Sensitivity to the Effects of Randomness. ACM Computing Surveys. 57(1). 1–40. 2 indexed citations
7.
Móro, Róbert, et al.. (2024). A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts. Zenodo (CERN European Organization for Nuclear Research). 6608–6625. 2 indexed citations
8.
Šimko, Jakub, et al.. (2024). Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation. Zenodo (CERN European Organization for Nuclear Research). 13148–13171. 1 indexed citations
9.
Razuvayevskaya, Olesya, Benjamin M. Wu, João Leite, et al.. (2024). Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification. PLoS ONE. 19(5). e0301738–e0301738. 8 indexed citations
10.
Srba, Ivan, et al.. (2024). Disinformation Capabilities of Large Language Models. Zenodo (CERN European Organization for Nuclear Research). 14830–14847. 11 indexed citations
11.
Móro, Róbert, Ivan Srba, Thái Hoàng Lê, et al.. (2023). MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark. Zenodo (CERN European Organization for Nuclear Research). 9960–9987. 14 indexed citations
12.
Srba, Ivan, et al.. (2023). Multilingual Previously Fact-Checked Claim Retrieval. 16477–16500. 4 indexed citations
13.
Srba, Ivan, et al.. (2022). Auditing YouTube’s Recommendation Algorithm for Misinformation Filter Bubbles. arXiv (Cornell University). 1(1). 1–33. 25 indexed citations
14.
Srba, Ivan, et al.. (2022). Monant Medical Misinformation Dataset. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2949–2959. 7 indexed citations
15.
Šimko, Jakub, et al.. (2022). Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics (Extended Abstract). Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 5349–5353.
16.
Móro, Róbert, et al.. (2021). Quantitative and qualitative analysis of linking patterns of mainstream and partisan online news media in Central Europe. Online Information Review. 46(5). 954–973. 6 indexed citations
17.
Srba, Ivan, et al.. (2019). Unravelling the basic concepts and intents of misbehavior in post-truth society. Dialnet (Universidad de la Rioja). 15(3). 421–428. 9 indexed citations
18.
Srba, Ivan, Miloš Savić, Mária Bieliková, Mirjana Ivanović, & Cesare Pautasso. (2019). Employing community question answering for online discussions in university courses: Students’ perspective. Computers & Education. 135. 75–90. 18 indexed citations
19.
Srba, Ivan & Mária Bieliková. (2014). Dynamic Group Formation as an Approach to Collaborative Learning Support. IEEE Transactions on Learning Technologies. 8(2). 173–186. 56 indexed citations
20.
Srba, Ivan & Mária Bieliková. (2010). Tracing Strength of Relationships in Social Networks. 13–16. 5 indexed citations

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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