172 citations · 729 across the 66 of their papers we have counts for
24 papers · 1 filter
Do You Think It's Biased? How To Ask For The Perception Of Media Bias
Timo Spinde, Christina Kreuter, Wolfgang Gaissmaier +3
Media coverage possesses a substantial effect on the public perception of events. The way media frames events can significantly alter the beliefs and perceptions of our society. Ne…
Detecting Cross-Language Plagiarism using Open Knowledge Graphs
Johannes Stegmüller, Fabian Bauer-Marquart, Norman Meuschke +3
Identifying cross-language plagiarism is challenging, especially for distant language pairs and sense-for-sense translations. We introduce the new multilingual retrieval model Cros…
Assisted Text Annotation Using Active Learning to Achieve High Quality with Little Effort
Franziska Weeber, Felix Hamborg, Karsten Donnay +1
Large amounts of annotated data have become more important than ever, especially since the rise of deep learning techniques. However, manual annotations are costly. We propose a to…
Academic Storage Cluster
Alexander von Tottleben, Cornelius Ihle, Moritz Schubotz +1
Decentralized storage is still rarely used in an academic and educational environment, although it offers better availability than conventional systems. It still happens that data…
ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts
Anastasia Zhukova, Felix Hamborg, Bela Gipp
Named entity recognition (NER) is an important task that aims to resolve universal categories of named entities, e.g., persons, locations, organizations, and times. Despite its com…
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection
Jan Philip Wahle, Nischal Ashok, Terry Ruas +3
A drastic rise in potentially life-threatening misinformation has been a by-product of the COVID-19 pandemic. Computational support to identify false information within the massive…
Newsalyze: Effective Communication of Person-Targeting Biases in News Articles
Felix Hamborg, Kim Heinser, Anastasia Zhukova +2
Media bias and its extreme form, fake news, can decisively affect public opinion. Especially when reporting on policy issues, slanted news coverage may strongly influence societal…
How to Effectively Identify and Communicate Person-Targeting Media Bias in Daily News Consumption?
Felix Hamborg, Timo Spinde, Kim Heinser +2
Slanted news coverage strongly affects public opinion. This is especially true for coverage on politics and related issues, where studies have shown that bias in the news may influ…
MathTools: An Open API for Convenient MathML Handling
André Greiner-Petter, Moritz Schubotz, Howard S. Cohl +1
Mathematical formulae carry complex and essential semantic information in a variety of formats. Accessing this information with different systems requires a standardized machine-re…
A Qualitative Evaluation of User Preference for Link-based vs. Text-based Recommendations of Wikipedia Articles
Malte Ostendorff, Corinna Breitinger, Bela Gipp
Literature recommendation systems (LRS) assist readers in the discovery of relevant content from the overwhelming amount of literature available. Despite the widespread adoption of…
XCoref: Cross-document Coreference Resolution in the Wild
Anastasia Zhukova, Felix Hamborg, Karsten Donnay +1
Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving co…
Towards Explaining STEM Document Classification using Mathematical Entity Linking
Philipp Scharpf, Moritz Schubotz, Bela Gipp
Document subject classification is essential for structuring (digital) libraries and allowing readers to search within a specific field. Currently, the classification is typically…
Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes
Anastasia Zhukova, Felix Hamborg, Bela Gipp
Established cross-document coreference resolution (CDCR) datasets contain event-centric coreference chains of events and entities with identity relations. These datasets establish…
Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons
Anastasia Zhukova, Felix Hamborg, Karsten Donnay +1
Unsupervised concept identification through clustering, i.e., identification of semantically related words and phrases, is a common approach to identify contextual primitives emplo…
zbMATH Open: API Solutions and Research Challenges
Matteo Petrera, Dennis Trautwein, Isabel Beckenbach +5
We present zbMATH Open, the most comprehensive collection of reviews and bibliographic metadata of scholarly literature in mathematics. Besides our website https://zbMATH.org which…
Incorporating Word Sense Disambiguation in Neural Language Models
Jan Philip Wahle, Terry Ruas, Norman Meuschke +1
We present two supervised (pre-)training methods to incorporate gloss definitions from lexical resources into neural language models (LMs). The training improves our models' perfor…
MBIC -- A Media Bias Annotation Dataset Including Annotator Characteristics
T. Spinde, L. Rudnitckaia, K. Sinha +3
Many people consider news articles to be a reliable source of information on current events. However, due to the range of factors influencing news agencies, such coverage may not a…
Newsalyze: Enabling News Consumers to Understand Media Bias
Felix Hamborg, Anastasia Zhukova, Karsten Donnay +1
News is a central source of information for individuals to inform themselves on current topics. Knowing a news article's slant and authenticity is of crucial importance in times of…
Towards Target-dependent Sentiment Classification in News Articles
Felix Hamborg, Karsten Donnay, Bela Gipp
Extensive research on target-dependent sentiment classification (TSC) has led to strong classification performances in domains where authors tend to explicitly express sentiment ab…
Enabling News Consumers to View and Understand Biased News Coverage: A Study on the Perception and Visualization of Media Bias
Timo Spinde, Felix Hamborg, Karsten Donnay +2
Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors.…
Evaluating Document Representations for Content-based Legal Literature Recommendations
Malte Ostendorff, Elliott Ash, Terry Ruas +3
Recommender systems assist legal professionals in finding relevant literature for supporting their case. Despite its importance for the profession, legal applications do not reflec…
Fast Linking of Mathematical Wikidata Entities in Wikipedia Articles Using Annotation Recommendation
Philipp Scharpf, Moritz Schubotz, Bela Gipp
Mathematical information retrieval (MathIR) applications such as semantic formula search and question answering systems rely on knowledge-bases that link mathematical expressions t…
Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection
Jan Philip Wahle, Terry Ruas, Norman Meuschke +1
The rise of language models such as BERT allows for high-quality text paraphrasing. This is a problem to academic integrity, as it is difficult to differentiate between original an…
Identifying Machine-Paraphrased Plagiarism
Jan Philip Wahle, Terry Ruas, Tomáš Foltýnek +2
Employing paraphrasing tools to conceal plagiarized text is a severe threat to academic integrity. To enable the detection of machine-paraphrased text, we evaluate the effectivenes…