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Florian Kunneman

Florian Kunneman has 2 papers in our library, in 2013–2026, most of them on Language models & pretraining, Sentiment & emotion; often with Antal van den Bosch.

2 papers in our library · 2013–2026

OpenAlex · ORCID · Wikidata · h-index 12 · 102 works · 784 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 52 times in our library · ⭐ Paper Stars ranking: #5141

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Utrecht UniversityUtrecht · Netherlands2023–2026 · 22 paperscurrent🎓Radboud University NijmegenNijmegen · Netherlands2011–2020 · 30 papersEmployment 2011–2016Employment 2016–2019🎓Vrije Universiteit AmsterdamAmsterdam · Netherlands2019–2024 · 13 papersEmployment since 2019🎓Center for Language StudiesNijmegen · Netherlands2012–2019 · 10 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksHuman-Computer Interaction · 1 workArts and Humanities · 1 workGeneral Social Sciences · 1 workLanguage and Linguistics · 1 workSocial Sciences · 1 work

🧭 Topics 2Research subjects and languages the work is about.Sentiment & emotion · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper

2010s

20131 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The perfect solution for detecting sarcasm in tweets #not (2013 · 274 citations)
    Sarcasm can invert the polarity of a message, often by using positive or exaggerated wording to express a negative view, which undermines sentiment analysis.
  2. Large Language Models Unpack Complex Political Opinions through Target-Stance Extraction (2026)
    Most computational studies of polarization sort political talk into coarse partisan bins. This misses how beliefs about specific policies, people and issues relate to one another. The authors test whether instruction-tuned LLMs can perform Target-Stance Extraction (TSE), which means finding what a post is about and…

 Co-authors here

1 co-author with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 52 times (of the 149,439 papers whose bibliographies we read); 41 citing papers with a page here →.

Updated

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