26 citations · 101 across the 19 of their papers we have counts for
21 papers
Emotion Embeddings $\unicode{x2014}$ Learning Stable and Homogeneous Abstractions from Heterogeneous Affective Datasets
Sven Buechel, Udo Hahn
Human emotion is expressed in many communication modalities and media formats and so their computational study is equally diversified into natural language processing, audio signal…
EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis
Sven Buechel, Udo Hahn
We describe EmoBank, a corpus of 10k English sentences balancing multiple genres, which we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) repres…
Towards Label-Agnostic Emotion Embeddings
Sven Buechel, Luise Modersohn, Udo Hahn
Research in emotion analysis is scattered across different label formats (e.g., polarity types, basic emotion categories, and affective dimensions), linguistic levels (word vs. sen…
GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines
Florian Borchert, Christina Lohr, Luise Modersohn +5
The lack of publicly accessible text corpora is a major obstacle for progress in natural language processing. For medical applications, unfortunately, all language communities othe…
What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way
Erik Faessler, Michel Oleynik, Udo Hahn
From 2017 to 2019 the Text REtrieval Conference (TREC) held a challenge task on precision medicine using documents from medical publications (PubMed) and clinical trials. Despite l…
Learning and Evaluating Emotion Lexicons for 91 Languages
Sven Buechel, Susanna Rücker, Udo Hahn
Emotion lexicons describe the affective meaning of words and thus constitute a centerpiece for advanced sentiment and emotion analysis. Yet, manually curated lexicons are only avai…