24 citations · 66 across the 11 of their papers we have counts for
13 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…
Empathic Conversations: A Multi-level Dataset of Contextualized Conversations
Damilola Omitaomu, Shabnam Tafreshi, Tingting Liu +5
Empathy is a cognitive and emotional reaction to an observed situation of others. Empathy has recently attracted interest because it has numerous applications in psychology and AI,…
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…
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…
Learning Word Ratings for Empathy and Distress from Document-Level User Responses
João Sedoc, Sven Buechel, Yehonathan Nachmany +2
Despite the excellent performance of black box approaches to modeling sentiment and emotion, lexica (sets of informative words and associated weights) that characterize different e…
A Time Series Analysis of Emotional Loading in Central Bank Statements
Sven Buechel, Simon Junker, Thore Schlaak +2
We examine the affective content of central bank press statements using emotion analysis. Our focus is on two major international players, the European Central Bank (ECB) and the U…
Learning Emotion from 100 Observations: Unexpected Robustness of Deep Learning under Strong Data Limitations
Sven Buechel, João Sedoc, H. Andrew Schwartz +1
One of the major downsides of Deep Learning is its supposed need for vast amounts of training data. As such, these techniques appear ill-suited for NLP areas where annotated data i…
Modeling Empathy and Distress in Reaction to News Stories
Sven Buechel, Anneke Buffone, Barry Slaff +2
Computational detection and understanding of empathy is an important factor in advancing human-computer interaction. Yet to date, text-based empathy prediction has the following ma…
Representation Mapping: A Novel Approach to Generate High-Quality Multi-Lingual Emotion Lexicons
Sven Buechel, Udo Hahn
In the past years, sentiment analysis has increasingly shifted attention to representational frameworks more expressive than semantic polarity (being positive, negative or neutral)…
JeSemE: A Website for Exploring Diachronic Changes in Word Meaning and Emotion
Johannes Hellrich, Sven Buechel, Udo Hahn
We here introduce a substantially extended version of JeSemE, an interactive website for visually exploring computationally derived time-variant information on word meanings and le…
Emotion Representation Mapping for Automatic Lexicon Construction (Mostly) Performs on Human Level
Sven Buechel, Udo Hahn
Emotion Representation Mapping (ERM) has the goal to convert existing emotion ratings from one representation format into another one, e.g., mapping Valence-Arousal-Dominance annot…
Modeling Word Emotion in Historical Language: Quantity Beats Supposed Stability in Seed Word Selection
Johannes Hellrich, Sven Buechel, Udo Hahn
To understand historical texts, we must be aware that language -- including the emotional connotation attached to words -- changes over time. In this paper, we aim at estimating th…