Diachronic Data Analysis Supports and Refines Conceptual Metaphor Theory

Metaphorically speaking, there is a wide river between computer-based data analysis methods on one side and Cognitive Linguistics (CL) and especially Conceptual Metaphor Theory (CMT) on the other side. Every now and then, a small boat attempts to cross this river, but our goal is to build a solid and lasting bridge. Less metaphorically, we need and want to address two different research communities simultaneously, each with its own concepts, ways of thinking and arguing, and discursive practices. To metaphor research, we present a statistical, data-based investigation that empirically analyzes long-standing conjectures and provides the first-ever exploration of the systematic structure underlying metaphors. To the Natural Language Processing community, we introduce metaphor theory as a basis of meaning emergence that can be quantitatively explored and whose understanding and integration into NLP methodologies hold great potential. Cognitive Linguistics and Data Analysis Data driven linguistics is a very active and lively research field, but there exists a blind spot regarding the findings of Cognitive Linguistics [1, 2] (CL for short). CL is an actively developing branch of linguistics without an established closed canon. It depends on several widely accepted premises.