%0 Conference Proceedings %T Comparing word2vec and GloVe for Automatic Measurement of MWE Compositionality %A Pickard, Thomas %Y Markantonatou, Stella %Y McCrae, John %Y Mitrović, Jelena %Y Tiberius, Carole %Y Ramisch, Carlos %Y Vaidya, Ashwini %Y Osenova, Petya %Y Savary, Agata %S Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons %D 2020 %8 December %I Association for Computational Linguistics %C online %F pickard-2020-comparing %X This paper explores the use of word2vec and GloVe embeddings for unsupervised measurement of the semantic compositionality of MWE candidates. Through comparison with several human-annotated reference sets, we find word2vec to be substantively superior to GloVe for this task. We also find Simple English Wikipedia to be a poor-quality resource for compositionality assessment, but demonstrate that a sample of 10% of sentences in the English Wikipedia can provide a conveniently tractable corpus with only moderate reduction in the quality of outputs. %U https://aclanthology.org/2020.mwe-1.12 %P 95-100