English Abstractness / Concreteness Ratings

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,
  46(3):904–911.

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