Conceptual Blending; Its Background and Its Strategy

Document Type : مقالات علمی پژوهشی

Authors
1 Ph.D. Candidate in Linguistics- Tarbiat Modares University –Tehran –Iran
2 Assistant Professor of Linguistics- Tarbiat Modares University –Tehran –Iran
3 Associate Professor of Linguistics- Tarbiat Modares University –Tehran –Iran
Abstract
Conceptual blending is one of the semantic approaches that concentrates on appearance and explanation of emergent concept or structure. Four mental spaces (at least two input spaces, a generic space and a blending space) have been proposed in this theory and to represent the emergent concepts or structures, we need to explain the relations between these spaces, inner-space and outer-space mapping, selective projection, composition, completion and elaboration. Conceptual metaphor and mental spaces are the inspiring theories for conceptual blending theories. Then, how to understand and infer the blending process to conclude in emergent structure and also theoretical needs to conceptual blending, based on its background, are the motives for the present study. To accomplish this, adequacy of conceptual blending in representing concepts that is activated while conceptualizing is reevaluated through some examples from Persian data (linguistic or even non-linguistic). The examples are taken from a variety of sources namely television advertisements, everyday expressions people use in their interactions, corpus data (Dadegan) and so on to explain the theory as well as possible. These data were analyzed based on four types of conceptual blending networks including simplex network, mirror network, single-scope network and double-scope network. For what is new in this research, we can say that not so many studies have been done in Persian using this theory and so rarely they have analyzed the data by illustrating them through the networks. As a matter of fact, if some studies have been taken place, they usually just sufficed to explain them. In addition, the outcome of the research on Persian provides the Persian data to be used in natural language processing specially in semantic scope. The results evince that using dynamic conceptualization in mental spaces, rejecting one-way and single mapping, applying selective projections, no being necessary to exist a counterpart for every element in mental spaces and not considering mental functions separate are all features that strengthen the adequacy of explanations of conceptual blending.


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