mlsanityData to 7 Oct 2026

Emotion Stimulus Detection in German News Headlines

arXiv 2107.12920 ↗First posted 27 Jul 2021cs.CLcited by 4

Not on the map. Why?

Abstract (arXiv)

Emotion stimulus extraction is a fine-grained subtask of emotion analysis that focuses on identifying the description of the cause behind an emotion expression from a text passage (e.g., in the sentence "I am happy that I passed my exam" the phrase "passed my exam" corresponds to the stimulus.). Previous work mainly focused on Mandarin and English, with no resources or models for German. We fill this research gap by developing a corpus of 2006 German news headlines annotated with emotions and 811 instances with annotations of stimulus phrases. Given that such corpus creation efforts are time-consuming and expensive, we additionally work on an approach for projecting the existing English GoodNewsEveryone (GNE) corpus to a machine-translated German version. We compare the performance of a conditional random field (CRF) model (trained monolingually on German and cross-lingually via projection) with a multilingual XLM-RoBERTa (XLM-R) model. Our results show that training with the German corpus achieves higher F1 scores than projection. Experiments with XLM-R outperform their respective CRF counterparts.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 13 of its 55 references that are in the map. First posted on arXiv 27 Jul 2021.

Builds on

13 of 55 references.

References · 13

  1. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  2. 2017DailyDialog: A Manually Labelled Multi-turn Dialogue Datasetcited by 649
  3. 2019Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Textscited by 82
  4. 2019GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perceptioncited by 37
  5. 2017Emotion Intensities in Tweetscited by 32
  6. 2020Appraisal Theories for Emotion Classification in Textcited by 27
  7. 2019Crowdsourcing and Validating Event-focused Emotion Corpora for German and Englishcited by 25
  8. 2019RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extractioncited by 24
  9. 2019Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characterscited by 23
  10. 2017A Question Answering Approach to Emotion Cause Extractioncited by 21
  11. 2020PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetrycited by 17
  12. 2020Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus Detectioncited by 8
1 more
  1. 2021Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotationscited by 6

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 1.

4 papers.

  1. 2022Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corporacited by 13
  2. 2021Multi-Task Learning with Sentiment, Emotion, and Target Detection to Recognize Hate Speech and Offensive Languagecited by 12
  3. 2023Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approachescited by 7
  4. 2022Modelling Emotion Dynamics in Song Lyrics with State Space Modelscited by 2