@inproceedings{koper-schulte-im-walde-2016-automatically,
title = "Automatically Generated Affective Norms of Abstractness, Arousal, Imageability and Valence for 350 000 {G}erman Lemmas",
author = {K{\"o}per, Maximilian and
Schulte im Walde, Sabine},
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1413",
pages = "2595--2598",
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: \url{http://www.ims.uni-stuttgart.de/data/affective_norms/}",
}
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%0 Conference Proceedings
%T Automatically Generated Affective Norms of Abstractness, Arousal, Imageability and Valence for 350 000 German Lemmas
%A Köper, Maximilian
%A Schulte im Walde, Sabine
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F koper-schulte-im-walde-2016-automatically
%X 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/
%U https://aclanthology.org/L16-1413
%P 2595-2598
Markdown (Informal)
[Automatically Generated Affective Norms of Abstractness, Arousal, Imageability and Valence for 350 000 German Lemmas](https://aclanthology.org/L16-1413) (Köper & Schulte im Walde, LREC 2016)
ACL