  In this work we analyze the performances of two of the most used word
embeddings algorithms, skip-gram and continuous bag of words on Italian
language. These algorithms have many hyper-parameter that have to be carefully
tuned in order to obtain accurate word representation in vectorial space. We
provide an accurate analysis and an evaluation, showing what are the best
configuration of parameters for specific tasks.
