Social Sciences Word Embeddings in FastText

These social science word embeddings in FastText have been created from 37,604 open access social science research papers from the social science access repository (https://www.gesis.org/ssoar/home). They are available in German and English. (skipgram model, n-grams with n≥3 and n≤6, different dimensions (100, 150, 200, 300, 500), five epochs, learning rate 0.05, five negative examples) Please cite: Schiffers, Ricardo, Dagmar Kern, and Daniel Hienert. 2022. "Evaluation of Word Embeddings for the Social Sciences." In <em>Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature</em>, edited by Stefania Degaetano, Anna Kazantseva, Nils Reiter, and Stan Szpakowicz, 1-6. Gyeongju: Association for Computational Linguistics. https://aclanthology.org/2022.latechclfl-1.1.