Automatisch generierte Normen für Emotionen & Affective Norms for 2.2m German Words & Analogie Dataset

1] Ratings for German

This resource contains a collection of 2.2million German words, rated on 9 affective norms. All ratings were obtained via a supervised learning algorithm that automatically calculates a numerical rating for each word and each affective attribute.

We applied this algorithm to four different rating types: anger, disgust, fear, joy, sadness, valence, arousal, concreteness, happiness.

All scores range from [0,10].

if you use the automatically extended norms please cite our work and the orgininal resource (see below), more details for about the references can be found in our paper - thank you!

• NRC Hashtag Emotion Lexicon (Mohammad and Kiritchenko,2015)
• Warriner et al. (2013)
• Dodds et al. (2011)
• Brysbaert et al. (2014)

2] German PV Analogie Dataset

The collection contains 685 BV-PV analogy pairs annotated for four categories, for details see the paper. Dataset can be downloaded here

Maximilian Köper, Sabine Schulte im Walde
Analogies in Complex Verb Meaning Shifts:The Effect of Affect in Semantic Similarity Models
In to appear NAACL 2018

Please consider to additional cite the training resource publication:

• NRC Hashtag Emotion Lexicon (Mohammad and Kiritchenko,2015)
• Warriner et al. (2013)
• Dodds et al. (2011)
• Brysbaert et al. (2014)

See or paper for the exact references.

The resources are freely available for education, research and other non-commercial purposes. For download please click here for the ratings or contact Maximilian Köper or Sabine Schulte im Walde to obtain the data.

The pv analogie dataset can be downloaded here.