Track E, led by Yadira Lizama Mué (CulturePlex Lab, Western Ontario University) will explore the power of NLP to study what textual data can tell us about art on a large scale. NLP is a field of Artificial Intelligence that centers around measuring human language to make it intelligible to machines. It combines the power of linguistics and computer science to contemplate the guidelines and structure of language and make intelligent systems fit for comprehension, breaking down, and separating significance from text and speech. We’ll learn a wide range of NLP topics, such as regular expressions, word tokenization, named-entity recognition, topics extraction, sentiment analysis, and text classification. We’ll also gain practical experience in the use of tools such as Spacy, alongside libraries that utilize deep learning to solve common NLP problems. We will have the opportunity to explore collections of texts related to art included in H.W.Wilson’s Art Full Text database, Project Muse, Wikipedia, and hundreds of media articles related to art exhibitions.