Conceptual Organization is Revealed by Consumer Activity Patterns.

ABSTRACT: Computational models using text corpora have proved useful in understanding the nature of language and human concepts. One appeal of this work is that text, such as from newspaper articles, should reflect human behaviour and conceptual organization outside the laboratory. However, texts do not directly reflect human activity, but instead serve a communicative function and are highly curated or edited to suit an audience. Here, we apply methods devised for text to a data source that directly reflects thousands of individuals' activity patterns. Using product co-occurrence data from nearly 1.3-m supermarket shopping baskets, we trained a topic model to learn 25 high-level concepts (or topics). These topics were found to be comprehensible and coherent by both retail experts and consume

SUBMITTER: Hornsby AN 

PROVIDER: S-EPMC7235073 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature