Language mediated mentalization: A proposed model
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Yair Neuman
Abstract
Mentalization describes the process through which we understand the mental states of oneself and others. In this paper, I present a computational semiotic model of mentalization and illustrate it through a worked-out example. The model draws on classical semiotic ideas, such as abductive inference and hypostatic abstraction, but pours them into new ideas and tools from natural language processing, machine learning, and neural networks, to form a novel model of language-mediated-mentalization.
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Articles in the same Issue
- Frontmatter
- Research Articles
- Spatializing food: Signs, spaces, and the legal (dis-)composition of what we eat
- A review of the comparative study of Mo Yan and Faulkner in China
- Expounding knowledge through explanations: Generic types and rhetorical-relational patterns
- A semiosic translation of the term “Bild” in both the Tractatus Logico-Philosophicus and The Philosophical Investigations
- Talking green and acting green are two different things: An experimental investigation of the relationship between implicit and explicit attitudes and low carbon consumer choice
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- Using semantic tagging to examine the American Dream and the Chinese Dream
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- Concepts of narrative, founding violence, and multiculturalism in the Americas: Greimas, Girard, and Kymlicka
- Language mediated mentalization: A proposed model
- Immanuel Kant on the philosophy of communicology: The tropic logic of rhetoric and semiotics
- Voice and bodily deixis as manifestation of performativity in written texts
- Review Articles
- Review of The semiotics of emoji: The rise of visual language in the age of the Internet
- The semiotics of intuition, care, and esotericism in education
- Book Review
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