90 citations · 210 across the 15 of their papers we have counts for
3 papers · 1 filter
Word-Emoji Embeddings from large scale Messaging Data reflect real-world Semantic Associations of Expressive Icons
Jens Helge Reelfs, Oliver Hohlfeld, Markus Strohmaier +1
We train word-emoji embeddings on large scale messaging data obtained from the Jodel online social network. Our data set contains more than 40 million sentences, of which 11 millio…
Joint Multiclass Debiasing of Word Embeddings
Radomir Popović, Florian Lemmerich, Markus Strohmaier
Bias in Word Embeddings has been a subject of recent interest, along with efforts for its reduction. Current approaches show promising progress towards debiasing single bias dimens…
The POLAR Framework: Polar Opposites Enable Interpretability of Pre-Trained Word Embeddings
Binny Mathew, Sandipan Sikdar, Florian Lemmerich +1
We introduce POLAR - a framework that adds interpretability to pre-trained word embeddings via the adoption of semantic differentials. Semantic differentials are a psychometric con…