Distributional semantics in linguistic and cognitive research

TLDR

Distributional semantics posits that word co‑occurrence statistics from text corpora can form semantic representations, a usage‑based approach that has attracted attention in both computational linguistics and cognitive science, though differing methods and contexts have led to parallel, largely independent research streams. The study seeks to uncover a general model of meaning that explains the commonalities across distributional approaches and formulates hypotheses about the format of semantic representations and their construction and processing by the human mind.

Abstract

The hypothesis that word co-occurrence statistics extracted from text corpora can provide a basis for semantic representations has been gaining growing attention both in computational linguistics and in cognitive science. The terms distributional, context-theoretic, corpusbased or statistical can all be used (almost interchangeably) to qualify a rich family of approaches to semantics that share a “usage-based” perspective on meaning, and assume that the statistical distribution of words in context plays a key role in characterizing their semantic behavior. Besides this common core, many differences exist depending on the specific mathematical and computational techniques, the type of semantic properties associated with text distributions, the definition of the linguistic context used to determine the combinatorial spaces of lexical items, etc. Yet, at a closer look, we may discover that the commonalities are more than we could expect prima facie, and that a general model of meaning can indeed be discerned behind the differences, a model that formulates specific hypotheses on the format of semantic representations, and on the way they are built and processed by the human mind. Methods for computational analysis of word distributional properties have been developed both in computational linguistics and in psychology. Because of the different aims of each field, these lines of research have typically proceeded totally in a parallel fashion, often ignoring each other. The drawbacks of this situation are clear: many