Concepts such as ​schizophrenia​, ​marriage or ​fact change through time. In philosophy,  these changes are studied in a small amount of scientific or scholarly texts at a time through very precise, subtle, manual analyses (close reading). In computational linguistics, the changes in question are studied in massive, generic corpora such as the whole of Wikipedia, by computational methods largely based on so-called ‘word embeddings’, representations of word meaning in a semantic space using vectors based purely on their surrounding words. The current challenge in philosophy is to obtain fine-grained analyses at a bigger scale (Betti & van den Berg 2016). The current challenge in computational linguistics is to detect non-trivial shifts of meaning, while increasing reliability by a firm methodological grasp of the real factors influencing the results (Hellrich & Hahn 2016).
In this project philosophers and computational linguists conduct an interdisciplinary pilot study with the aim of combining the strengths of both fields. We will rely on a test case from a corpus comprising the writings of the American philosopher W. V. Quine. The corpus is small from a computational linguistics point of view, but rather big from a philosophical point of view. The philosophers will provide a dataset, a test case and an evaluation set centering around subtle shifts on a number of concepts (such as ​science​,
fact ​, ​intuition​). The computational linguists will apply an adaptation of word embeddings models for tiny data for this type of texts along the lines of Herbelot and Baroni 2017’s nonce2vec designed to learn embeddings from tiny data. The focus of the project will be methodological. The project will be considered successful if, next to a software release, an adequate evaluation method for this type of data and type of interdisciplinary projects will be developed at the end of the project.