Abstract
This paper presents a collection of 350,000 German lemmatised words, rated on four psycholinguistic affective attributes. All ratings were obtained via a supervised learning algorithm that can automatically calculate a numerical rating of a word. We applied this algorithm to abstractness, arousal, imageability and valence. Comparison with human ratings reveals high correlation across all rating types. The full resource is publically available at: http://www.ims.uni-stuttgart.de/data/affective_norms/- Anthology ID:
- L16-1413
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 2595–2598
- Language:
- URL:
- https://aclanthology.org/L16-1413
- DOI:
- Cite (ACL):
- Maximilian Köper and Sabine Schulte im Walde. 2016. Automatically Generated Affective Norms of Abstractness, Arousal, Imageability and Valence for 350 000 German Lemmas. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2595–2598, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Automatically Generated Affective Norms of Abstractness, Arousal, Imageability and Valence for 350 000 German Lemmas (Köper & Schulte im Walde, LREC 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/L16-1413.pdf