---
title: "Martin Potthast — author profile and papers"
description: "Martin Potthast, University of Kassel: 5 papers on Elamur Research (2017–2019), h-index 45 — affiliations, topics, co-authors and who cites them in our…"
canonical: "https://research.elamur.ai/free/en/authors/martin-potthast/"
---
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# Martin Potthast

Martin Potthast's papers here belong to natural language processing and are often built around shared evaluation: assembling new corpora and organising tasks in which many systems are compared on the same data. Two lines run through them. One asks whether the style of a news article can reveal political bias or unreliability. The other concerns multilingual syntactic parsing in the Universal Dependencies framework. A further paper turns to automatic summarization. The methods are corpus construction from web sources, classifiers tested on material unseen in training, and benchmark scoring of submitted systems.

The most cited work, [A Stylometric Inquiry into Hyperpartisan and Fake News](https://md.research.elamur.ai/free/en/papers/potthast-2018-stylometric-inquiry-into-hyperpartisan-fake/) (2018), introduced the BuzzFeed-Webis Fake News Corpus 2016. It holds 1,627 articles from nine publishers, each rated for veracity by journalists. The paper compares style-based with topic-based classifiers and evaluates them on publishers held out from training. The [CoNLL 2017 Shared Task](https://md.research.elamur.ai/free/en/papers/ud-2017-zeman-conll-2017-shared-task-multilingual/) asked participating systems to go from raw text, without gold tokenization or tags, to dependency trees in 49 languages, including a few surprise languages with almost no training data. [TL;DR: Mining Reddit to Learn Automatic Summarization](https://md.research.elamur.ai/free/en/papers/volske-2017-tl-dr-mining-reddit-learn/) (2017) used the summary lines that Reddit users add to their own long posts. From these it built Webis-TLDR-17, roughly 4 million pairs of informal content and summary.

The newest papers here, from 2018 and 2019, continue both lines. [SemEval-2019 Task 4: Hyperpartisan News Detection](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/) set up a shared task on recognising one-sided political news. It offers two English corpora: a small one labeled per article by crowd workers and a large one labeled from publisher-level bias lists. Teams handed in their software rather than its predictions. The [CoNLL 2018 Shared Task](https://md.research.elamur.ai/free/en/papers/ud-2018-zeman-conll-2018-shared-task-multilingual/) repeated the raw-text parsing setup on 82 test treebanks and added the MLAS and BLEX metrics, which also score morphology and lemmas.

Potthast is currently affiliated with the University of Kassel, the Hessian Center for Artificial Intelligence and the Center for Scalable Data Analytics and Artificial Intelligence in Dresden, after earlier periods at Leipzig University and Bauhaus-Universität Weimar. Frequent co-authors include [Johannes Kiesel](https://md.research.elamur.ai/free/en/authors/johannes-kiesel/), [Benno Stein](https://md.research.elamur.ai/free/en/authors/benno-stein/) and, on the [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) tasks, [Daniel Zeman](https://md.research.elamur.ai/free/en/authors/daniel-zeman/).

5 papers on this site · 2017–2019

current affiliation [University of Kassel](https://ror.org/04zc7p361), Kassel, Germany; [Hessian Center for Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/hessian-center-for-artificial-intelligence/), Darmstadt, Germany; [Center for Scalable Data Analytics and Artificial Intelligence](https://md.research.elamur.ai/free/en/universities/center-for-scalable-data-analytics-and-artificial-intelligence/), Dresden, Germany

Martin Potthast has 5 papers on this site, in 2017–2019, most of them on [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/), [Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/), [Summarization](https://md.research.elamur.ai/free/en/topics/summarization/); often with [Benno Stein](https://md.research.elamur.ai/free/en/authors/benno-stein/), [Daniel Zeman](https://md.research.elamur.ai/free/en/authors/daniel-zeman/), [Filip Ginter](https://md.research.elamur.ai/free/en/authors/filip-ginter/). 2 of them are among the papers [Mova](https://md.research.elamur.ai/free/en/projects/mova/) reads.

[OpenAlex](https://openalex.org/A5083712311) · [ORCID](https://orcid.org/0000-0003-2451-0665) · [**h-index 45**](https://openalex.org/authors/A5083712311) · [559 works](https://openalex.org/works?filter=author.id:A5083712311) · [8 785 citations](https://openalex.org/works?filter=author.id:A5083712311&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[5 works on this site](https://md.research.elamur.ai/free/en/authors/martin-potthast/#papers) · [2 037 citations in our library](https://md.research.elamur.ai/free/en/authors/martin-potthast/cited-by/) · 4 more works in our library

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

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Martin+Potthast) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Martin+Potthast) · [dblp](https://dblp.org/search?q=Martin+Potthast) · [ACL Anthology](https://aclanthology.org/search/?q=Martin+Potthast)

## Affiliations

- [Center for Scalable Data Analytics and Artificial Intelligence](https://md.research.elamur.ai/free/en/universities/center-for-scalable-data-analytics-and-artificial-intelligence/) · Dresden, Germany —current · 2021–2026 on 125 papers
- [University of Kassel](https://ror.org/04zc7p361) · Kassel, Germany —current · 2024–2026 on 71 papers · employment (Wikidata)
- [Hessian Center for Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/hessian-center-for-artificial-intelligence/) · Darmstadt, Germany —current · 2024–2026 on 35 papers
- [Bauhaus-Universität Weimar](https://md.research.elamur.ai/free/en/universities/bauhaus-universitat-weimar/) · Weimar, Germany —2006–2025 on 88 papers · education (Wikidata)
- [Leipzig University](https://md.research.elamur.ai/free/en/universities/leipzig-university/) · Leipzig, Germany —2012–2024 on 255 papers
- [University of Groningen](https://md.research.elamur.ai/free/en/universities/university-of-groningen/) · Groningen, Netherlands —2023–2024 on 3 papers
- [Friedrich Schiller University Jena](https://md.research.elamur.ai/free/en/universities/friedrich-schiller-university-jena/) · Jena, Germany —2023 on 2 papers
- [Martin Luther University Halle-Wittenberg](https://md.research.elamur.ai/free/en/universities/martin-luther-university-halle-wittenberg/) · Halle, Germany —2020–2021 on 2 papers

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

## Topics

[Universal Dependencies 2](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Multilingual & cross-lingual NLP 2](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Summarization 1](https://md.research.elamur.ai/free/en/topics/summarization/)

## Works by year

### 2010s

[**2019** 1 paper](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/) · [**2018** 2 papers](https://md.research.elamur.ai/free/en/authors/martin-potthast/year/2018/) · [**2017** 2 papers](https://md.research.elamur.ai/free/en/authors/martin-potthast/year/2017/)

## Papers

The most cited first (OpenAlex and our library).

1. **[A Stylometric Inquiry into Hyperpartisan and Fake News](https://md.research.elamur.ai/free/en/papers/potthast-2018-stylometric-inquiry-into-hyperpartisan-fake/)** *(2018 · 808 citations)* Potthast and colleagues ask whether writing style alone can flag problematic political news before it spreads.
2. **[CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies](https://md.research.elamur.ai/free/en/papers/ud-2017-zeman-conll-2017-shared-task-multilingual/)** *(2017 · 604 citations)* The shared task asks systems to parse raw text, with no gold tokenization, sentence splitting or tags, into UD trees for 49 languages.
3. **[SemEval-2019 Task 4: Hyperpartisan News Detection](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/)** *(2019 · 335 citations)* This paper describes SemEval-2019 Task 4, a shared task on deciding whether an online news article is hyperpartisan, meaning it presents one political side while ignoring or aggressively attacking opposing views.
4. **[CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies](https://md.research.elamur.ai/free/en/papers/ud-2018-zeman-conll-2018-shared-task-multilingual/)** *(2018 · 316 citations)* This overview describes the second CoNLL shared task on parsing raw text into UD. Systems start from raw text, with no gold segmentation or tags, and are scored on 82 test treebanks, with macro-averaged LAS and two new metrics, MLAS (labels plus morphological features) and BLEX (lemmas plus labels). Eight new…
5. **[TL;DR: Mining Reddit to Learn Automatic Summarization](https://md.research.elamur.ai/free/en/papers/volske-2017-tl-dr-mining-reddit-learn/)** *(2017 · 202 citations)* Neural abstractive summarizers need very large training sets, and nearly all large English corpora for this task come from news.

## Also in our library

4 more works of theirs are in our library without a page here yet; they will appear as we publish them.

## Co-authors here

12 of 37 co-authors with a page, the most papers together first.

- [Benno Stein](https://md.research.elamur.ai/free/en/authors/benno-stein/) ×3
- [Daniel Zeman](https://md.research.elamur.ai/free/en/authors/daniel-zeman/) ×2
- [Filip Ginter](https://md.research.elamur.ai/free/en/authors/filip-ginter/) ×2
- [Jan Hajič](https://md.research.elamur.ai/free/en/authors/jan-hajic/) ×2
- [Joakim Nivre](https://md.research.elamur.ai/free/en/authors/joakim-nivre/) ×2
- [Johannes Kiesel](https://md.research.elamur.ai/free/en/authors/johannes-kiesel/) ×2
- [Martin Popel](https://md.research.elamur.ai/free/en/authors/martin-popel/) ×2
- [Milan Straka](https://md.research.elamur.ai/free/en/authors/milan-straka/) ×2
- [Slav Petrov](https://md.research.elamur.ai/free/en/authors/slav-petrov/) ×2
- [Ali Elkahky](https://md.research.elamur.ai/free/en/authors/ali-elkahky/)
- [Aljoscha Burchardt](https://md.research.elamur.ai/free/en/authors/aljoscha-burchardt/)
- [Anna Nedoluzhko](https://md.research.elamur.ai/free/en/authors/anna-nedoluzhko/)

## Cited by

Papers of our library cite their works 2 037 times (of the 140 884 papers whose bibliographies we read); [212 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/martin-potthast/cited-by/).