CLDMSep 25, 2022

Diachronic Data Analysis Supports and Refines Conceptual Metaphor Theory

arXiv:2209.12234v22 citationsh-index: 8
Originality Synthesis-oriented
AI Analysis

This work addresses the need for empirical grounding in metaphor theory for researchers in linguistics and NLP, offering a quantitative basis for meaning emergence, though it appears incremental as it builds on existing theory with new data analysis.

The paper tackled the problem of empirically validating and refining conceptual metaphor theory by conducting a statistical, data-based analysis of long-standing conjectures and systematic features of metaphors, resulting in a first-ever empirical exploration that supports and refines the theory.

As a contribution to metaphor analysis, we introduce a statistical, data-based investigation with empirical analysis of long-standing conjectures and a first-ever empirical exploration of the systematic features of metaphors. Conversely, this also makes metaphor theory available as a basis of meaning emergence that can be quantitatively explored and integrated into the framework of NLP.

Foundations

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