Michael Tschuggnall

502 total citations
20 papers, 142 citations indexed

About

Michael Tschuggnall is a scholar working on Artificial Intelligence, Computer Networks and Communications and Health Informatics. According to data from OpenAlex, Michael Tschuggnall has authored 20 papers receiving a total of 142 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 3 papers in Computer Networks and Communications and 3 papers in Health Informatics. Recurrent topics in Michael Tschuggnall's work include Authorship Attribution and Profiling (11 papers), Natural Language Processing Techniques (10 papers) and Topic Modeling (9 papers). Michael Tschuggnall is often cited by papers focused on Authorship Attribution and Profiling (11 papers), Natural Language Processing Techniques (10 papers) and Topic Modeling (9 papers). Michael Tschuggnall collaborates with scholars based in Austria, Germany and Switzerland. Michael Tschuggnall's co-authors include Günther Specht, Martin Potthast, Benno Stein, Efstathios Stamatatos, Walter Daelemans, Mike Kestemont, Michael J. Fischer, Gerhard Rumpold, Ben Verhoeven and Bernhard Holzner and has published in prestigious journals such as BMC Medical Informatics and Decision Making, Diagnostics and Informatics in Medicine Unlocked.

In The Last Decade

Michael Tschuggnall

18 papers receiving 113 citations

Peers

Michael Tschuggnall
Comparison fields: 5 of 48
  • Artificial Intelligence 114
  • Information Systems 25
  • Health Informatics 10
  • Computer Networks and Communications 8
  • Safety Research 8
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Citations per field, relative to Michael Tschuggnall
Michael Tschuggnall · 1×
Citations per year, relative to Michael Tschuggnall
Michael Tschuggnall · 1×

Countries citing papers authored by Michael Tschuggnall

Since Specialization
Citations

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

Fields of papers citing papers by Michael Tschuggnall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Tschuggnall

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Tschuggnall. A scholar is included among the top collaborators of Michael Tschuggnall 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 Michael Tschuggnall. Michael Tschuggnall 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
# Work Indexed citations
1 1
2 2
3 27
4 3
5 1
6 0
7
Overview of the Style Change Detection Task at PAN 2019.
5
8 3
9 2
10
Overview of the Author Identification Task at PAN-2018: Cross-domain Authorship Attribution and Style Change Detection.
36
11
Dynamic Parameter Search for Cross-Domain Authorship Attribution: Notebook for PAN at CLEF 2018.
1
12
Overview of the Author Identification Task at PAN-2017: Style Breach Detection and Author Clustering.
14
13
Hierarchical Multilabel Classification and Voting for Genre Classification.
1
14
Clustering by Authorship Within and Across Documents.
21
15
Automatic Decomposition of Multi-Author Documents Using Grammar Analysis.
2
16
What Grammar Tells About Gender and Age of Authors
0
17 9
18
Detecting plagiarism in text documents through grammar-analysis of authors
6
19 1
20 7

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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