Johann Petrak

738 total citations
15 papers, 395 citations indexed

About

Johann Petrak is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Johann Petrak has authored 15 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Sociology and Political Science. Recurrent topics in Johann Petrak's work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Data Mining Algorithms and Applications (3 papers). Johann Petrak is often cited by papers focused on Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Data Mining Algorithms and Applications (3 papers). Johann Petrak collaborates with scholars based in United Kingdom, Austria and France. Johann Petrak's co-authors include Diana Maynard, Kalina Bontcheva, Johannes Fürnkranz, Marieke van Erp, Genevieve Gorrell, Raphaël Troncy, Leon Derczynski, Giuseppe Rizzo, Xingyi Song and Ye Jiang and has published in prestigious journals such as PLoS ONE, Scientometrics and Information Processing & Management.

In The Last Decade

Johann Petrak

15 papers receiving 363 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johann Petrak United Kingdom 8 311 92 67 28 27 15 395
Tom Kenter Netherlands 9 391 1.3× 130 1.4× 30 0.4× 38 1.4× 30 1.1× 19 490
Hsinchun Chen United States 7 142 0.5× 104 1.1× 50 0.7× 17 0.6× 38 1.4× 7 275
Stijn De Saeger Japan 11 352 1.1× 69 0.8× 41 0.6× 27 1.0× 28 1.0× 26 398
Mücahid Kutlu Türkiye 12 293 0.9× 117 1.3× 78 1.2× 43 1.5× 34 1.3× 44 409
Mikołaj Morzy Poland 9 91 0.3× 73 0.8× 75 1.1× 24 0.9× 19 0.7× 40 252
Rodrigo Agerri Spain 14 462 1.5× 58 0.6× 37 0.6× 39 1.4× 26 1.0× 47 536
You Wu United States 10 243 0.8× 127 1.4× 101 1.5× 89 3.2× 36 1.3× 25 354
Marina Litvak Israel 11 418 1.3× 97 1.1× 39 0.6× 22 0.8× 32 1.2× 52 493
Justin Martineau United States 9 460 1.5× 163 1.8× 39 0.6× 44 1.6× 23 0.9× 17 571
Faiçal Azouaou Algeria 10 300 1.0× 80 0.9× 29 0.4× 10 0.4× 19 0.7× 28 362

Countries citing papers authored by Johann Petrak

Since Specialization
Citations

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

Fields of papers citing papers by Johann Petrak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johann Petrak

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

All Works

15 of 15 papers shown
1.
Song, Xingyi, et al.. (2021). Classification aware neural topic model for COVID-19 disinformation categorisation. PLoS ONE. 16(2). e0247086–e0247086. 37 indexed citations
2.
Maynard, Diana, Benedetto Lepori, Johann Petrak, Xingyi Song, & Philippe Larédo. (2020). Using ontologies to map between research data and policymakers’ presumptions: the experience of the KNOWMAK project. Scientometrics. 125(2). 1275–1290. 4 indexed citations
3.
Jiang, Ye, Johann Petrak, Xingyi Song, Kalina Bontcheva, & Diana Maynard. (2019). Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network. 840–844. 28 indexed citations
4.
Song, Xingyi, Johann Petrak, & Angus Roberts. (2018). A Deep Neural Network Sentence Level Classification Method with Context Information. 900–904. 13 indexed citations
5.
Zhang, Ziqi, Johann Petrak, & Diana Maynard. (2018). Adapted TextRank for Term Extraction: A Generic Method of Improving Automatic Term Extraction Algorithms. Procedia Computer Science. 137. 102–108. 20 indexed citations
6.
Aker, Ahmet, et al.. (2017). An Extensible Multilingual Open Source Lemmatizer. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 40–45. 3 indexed citations
7.
Derczynski, Leon, Diana Maynard, Giuseppe Rizzo, et al.. (2014). Analysis of named entity recognition and linking for tweets. Information Processing & Management. 51(2). 32–49. 207 indexed citations
8.
Fürnkranz, Johannes, Johann Petrak, Pavel Brazdil, & Carlos Soares. (2002). On the Use of Fast Subsampling Estimates for Algorithm Recommendation. 4 indexed citations
9.
Seewald, Alexander K., Johann Petrak, & Gerhard Widmer. (2001). Hybrid Decision Tree Learners with Alternative Leaf Classifiers: An Empirical Study. The Florida AI Research Society. 407–411. 11 indexed citations
10.
Fürnkranz, Johannes & Johann Petrak. (2001). An Evaluation of Landmarking Variants. 41 indexed citations
11.
Fürnkranz, Johannes, Johann Petrak, & Robert Trappl. (1997). Knowledge discovery in international conflict databases. Applied Artificial Intelligence. 11(2). 91–118. 13 indexed citations
12.
Trappl, Robert, Johannes Fürnkranz, & Johann Petrak. (1996). Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases. European Conference on Artificial Intelligence. 453–457. 7 indexed citations
13.
Fürnkranz, Johannes, Johann Petrak, Robert Trappl, & Jacob Bercovitch. (1994). Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome. 2 indexed citations
14.
Petrak, Johann, Robert Trappl, & Johannes Fürnkranz. (1994). The Potential Contribution of AI to the Avoidance of Crises and Wars: Using CBR Methods with the KOSIMO Database of Conflicts. 2 indexed citations
15.
Ehrendorfer, Friedrich, et al.. (1980). Windkan�le f�r die Untersuchung anemochorer Verbreitungseinheiten. Plant Systematics and Evolution. 136(1-2). 1–6. 3 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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