Resources for Emotion Analysis
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Corpus
- Author
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Roman Klinger et al.
- Description
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This page collects and publishes ressources created at IMS related to emotion and sentiment analysis.
- Emotion Intensity Predictions for Nonsense-Words (WASSA 2022)
- MMemo (WASSA 2022): Multi-Modal Emotion and Stimulus Corpus of Reddit Posts
- Gersti (KONVENS 2021): German Emotion Stimulus Corpus
- Emotion Components (KONVENS 2021): CPMEmotion-Corpus
- deISEAR/enISEAR (ACL 2019): Event-focused Emotion Corpora for German and English, annotated with crowdsourcing (2019)
- Emotion Appraisals (COLING 2020): With additional information on appraisals (2020)
- Relational Emotions (NAACL 2019): Emotion relation corpus for the recognition of emotional relations of characters in fan fiction (2019)
- German Satire Detection Corpus (NAACL 2019): Corpora and Models for German Satire Detection (2019)
- REMAN (NAACL 2019): Literature corpus annotated with experiencer, cause, target, trigger words, emotions (2018)
- Unified Emotions (COLING 2018): Unified corpora for emotion classification (2018)
- Emotion Intensifiers: WASSA 2019, DSAA 2018): Resources for intensifier modelling in the context of emotions (2018, 2019)
- Models and resources for emotion intensity prediction (2018)
- SSEC (WASSA 2017): Stance Sentiment Emotion Corpus (2017)
- Multimodal Emotions (NLDB 2017): Twitter corpus for emotion classification under consideration of visual and textual information. (2017)
- Irony Sarcasm Corpus (ESWC 2016): A corpus to distinguish between irony and sarcasm. (2016)
- SCARE (LREC 2016): SCARE - The Sentiment Corpus of App Reviews with Fine-grained Annotations in German (2016)
- German dictionaries for emotion analysis (2016)
- German and English sentiment analysis corpora, annotated with aspects and subjective phrases (2014) with machine translated sentences for both languages (2015)
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Roman Klinger
Prof. Dr.Adjunct Professor