# Roman Klinger

> researcher

**Wikidata**: [Q30439210](https://www.wikidata.org/wiki/Q30439210)  
**Source**: https://4ort.xyz/entity/roman-klinger

## Summary
Roman Klinger is a German computer scientist and linguist specializing in natural language processing and digital humanities. He is a professor at the University of Stuttgart and has made significant contributions to computational linguistics research.

## Biography
- Born: Not specified
- Nationality: German
- Education: PhD in Computer Science from Technical University of Dortmund (2010), Diploma in Computer Science from Technical University of Dortmund (2006)
- Known for: Research in natural language processing and digital humanities
- Employer(s): University of Stuttgart (current), Bielefeld University, University of Massachusetts Amherst (visiting professor)
- Field(s): Computer science, linguistics, natural language processing, digital humanities

## Contributions
Roman Klinger has built a substantial research career in natural language processing and computational linguistics. He has published extensively in the field, with his work appearing in major conferences and journals. His research focuses on sentiment analysis, emotion detection in text, and biomedical text mining. Klinger has developed and maintained several open-source software tools for NLP tasks, contributing to the broader research community. He has supervised numerous PhD students and postdocs, helping to train the next generation of computational linguists. His work has been cited thousands of times, indicating significant impact on the field. Klinger has also served on program committees for major NLP conferences and journals, helping to shape the direction of research in the field.

## FAQs
### Q: What is Roman Klinger's main area of research?
A: Roman Klinger specializes in natural language processing, with particular focus on sentiment analysis, emotion detection in text, and biomedical text mining applications.

### Q: Where does Roman Klinger currently work?
A: Roman Klinger is a professor at the University of Stuttgart, where he has worked since 2014, with a promotion to full professor in 2023.

### Q: What is Roman Klinger's educational background?
A: Klinger earned his Diploma in Computer Science and PhD in Computer Science from the Technical University of Dortmund in 2006 and 2010 respectively.

## Why They Matter
Roman Klinger matters because he has advanced the field of natural language processing through both theoretical contributions and practical tools. His work on emotion and sentiment analysis has helped bridge the gap between computational methods and human language understanding. By developing open-source software and publishing extensively, he has made NLP techniques more accessible to researchers worldwide. His mentorship of students and service to the academic community through conference organization and journal editing has helped shape the next generation of computational linguists. Without his contributions, the field would lack important tools and methodologies for analyzing emotional and sentiment content in text, which has applications ranging from social media analysis to biomedical research.

## Notable For
- Professor of Natural Language Processing at University of Stuttgart since 2023
- Extensive publication record in top NLP and computational linguistics venues
- Developer of multiple open-source NLP tools and libraries
- Supervisor of numerous PhD students in computational linguistics
- Visiting professor at University of Massachusetts Amherst in 2013

## Body
### Academic Career
Roman Klinger's academic journey began with his Diploma in Computer Science from Technical University of Dortmund in 2006, followed by his PhD in 2010 under the supervision of Günter Rudolph. His early career included postdoctoral positions at Fraunhofer Institute for Algorithms and Scientific Computing (2011-2012) and Bielefeld University (2013-2015). He joined the University of Stuttgart in 2014 as a substitute teacher, becoming a permanent faculty member in 2015 and achieving full professorship in 2023.

### Research Focus
Klinger's research primarily focuses on natural language processing with applications in sentiment analysis, emotion detection, and biomedical text mining. His work bridges computer science and linguistics, contributing to both theoretical understanding and practical applications of computational text analysis. He has developed methods for automatically detecting emotions and sentiments in text, which has applications in social media monitoring, customer feedback analysis, and psychological research.

### Publications and Impact
With a DBLP author ID of 21/4183 and a Google Scholar profile, Klinger has published extensively in the field. His work has been cited thousands of times, indicating significant influence on the research community. He maintains an active presence on academic platforms and social media, with a Twitter following of over 1,000 researchers and practitioners.

### Open Source Contributions
Klinger is committed to open science, maintaining GitHub repositories with NLP tools and code that support reproducible research. His open-source contributions make advanced NLP techniques accessible to researchers who might not have the resources to develop such tools independently.

### Academic Service
Beyond his research, Klinger serves the academic community through editorial roles, conference organization, and program committee membership for major NLP conferences. This service helps maintain the quality and direction of research in the field.

## Schema Markup
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## References

1. Integrated Authority File
2. Mathematics Genealogy Project
3. [Source](https://github.com/hennyu/dhd-chronicles/)
4. [Source](https://www.uni-bamberg.de/nlproc/team/prof-dr-roman-klinger/)
5. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/20651713)
6. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/19541815)
7. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3167985)
8. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3168018)
9. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3168001)
10. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3167991)
11. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3168006)
12. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3168003)
13. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0002-2014-6619/employment/3167997)
14. [Source](http://www.zfdg.de/node/285)
15. Zeitschrift für digitale Geisteswissenschaften
16. [Source](https://data.dnb.de/opendata/authorities-gnd-person_lds.rdf.gz)
17. [Source](https://twitter.com/roman_klinger)