Semantic spaces is a useful tool used to measure the semantic distance between words, and one of the most prominent methods for creating semantic spaces is Latent Semantic Analysis. LSA was originally developed as a document retrieval method to improve word matching approaches but is applicable to cognitive science and computer assisted educational research. LSA is a data-driven algorithm to use on text corpora and provides a high-dimensional semantic space where each word is represented as a vector in the semantic space, and where related words are located closer to each other.