Across disciplines, researchers are eager to gain insight into empirical features of abstract vs. concrete concepts and words. In the first part of this course we present an overview of the cognitive science literature which reports extensive analyses of how concrete concepts are processed, with however little consensus about the nature of abstract concepts. In the second part of this course we look into this dichotomy from a computational perspective, where the inclusion of information regarding the concreteness of words has been demonstrated to play a key role across NLP tasks, such as the automatic identification of figurative language. Additionally, we describe and discuss the procedures of collecting human-generated ratings of abstractness and their usage for both communities. Overall, this course thus aims at introducing and discussing cognitive and computational resources and empirical studies in order to understand the role and application of abstractness in large-scale data-driven models.
Course Requirements: bring with you a laptop or tablet that can connect to the wifi. We will work together online (no programming experience required).Materials (password protected): here