English Abstractness / Concreteness Ratings

A collection of English concreteness / abstractness norms for 3 million English words and Multiword expression

English Abstractness / Concreteness Ratings

Maximilian Köper & Sabine Schulte im Walde

We created a new collection of English concreteness / abstractness norms for 3 million English words and Multiword expression. We relied on the google pretrained vectors from word2vec which are available here : GoogleNews-vectors-negative300

The neural network implementation used in our experiements is based on this implementation

 Some (random) example words:

  • razor_blade 9.651
  • Oreo_cookies 9.392
  • toilet_paper 9.002
  • chocolate 9.171
  • pizza 9.013
  • ideals 0.083
  • endlessly 0.075
  • irresponsibly 0.058

Our paper describing how we created the resource [PDF]:

  • Maximilian Köper, Sabine Schulte im Walde
    Improving Verb Metaphor Detection by Propagating Abstractness to Words, Phrases and Individual Senses
    In: Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications

Please consider to also cite the publication of the used training data: 

  • Brysbaert, M., Warriner, B., and Kuperman, V. (2014).
    Concreteness ratings for 40 thousand generally known
    english word lemmas. Behavior Research Methods,

For acessing the ressource contact Maximilian Köper or try this download link

This image shows Sabine Schulte im Walde

Sabine Schulte im Walde

Prof. Dr.

Akademische Rätin (Associate Professor)

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