sensequantitative

Sensequantitative is a research framework that combines qualitative interpretation of semantic sense with quantitative measurement to study how words carry distinct meanings across contexts. By treating sense as a measurable dimension, it enables systematic comparison of sense distributions within and across corpora, genres, or time periods. The term has appeared in linguistics and data-science discussions since the late 2010s.

Methodology typically uses established sense inventories such as WordNet or domain ontologies, with word sense disambiguation to assign senses to occurrences. After labeling, researchers compute quantitative metrics—sense frequency, entropy of distributions, shifts over time, and co-occurrence networks—and apply statistical models or machine learning to relate sense use to outcomes.

Applications appear in social sciences, marketing, media studies, and digital humanities. Sensequantitative can reveal framing effects on meaning, track how technical jargon evolves, or compare sense usage across languages or communities.

Challenges include reliance on quality sense inventories, accuracy of disambiguation, cross-linguistic transferability, and risk of oversimplifying nuanced meaning. Interpretability and citation bias in corpora are ongoing concerns.

As a hybrid of quantitative linguistics and discourse analysis, sensequantitative aligns with corpus linguistics and semantic technology. Future work aims to integrate multilingual inventories and contextual embeddings to capture dynamic meaning more accurately.