WORDS, the building blocks of LANGUAGE, are signs that represent different kinds of CATEGORIES. Some words define categories of concrete entities (such as cat or table) while others define abstract entities (such as belief, empathy). Some words define generic categories that include within them different entities (such as the word vehicle, or art) while others define more specific categories (such as tandem, or Impressionism).
To derive meaning from our experiences, we construct different types of categories in our minds through abstraction mechanisms and label them using the words that our language provides. CONCRETENESS and SPECIFICITY are two fundamental variables that characterize the meaning of words and are involved in the mental processes of abstraction.
However, when the mechanisms and effects of abstraction are studied, researchers with different training tend to focus on different aspects of the phenomenon of abstraction. In particular, psychologists and cognitive scientists tend to focus on the variable called 'concreteness,' while linguists and computer scientists tend to focus on the variable called 'specificity.' These different and partial definitions of the phenomenon of abstraction often generate misunderstandings in interdisciplinary debates and hinder theoretical development.
This is also due to the fact that where there are large-scale collections of native speaker-generated judgments related to the concreteness of words, there are no speaker-generated lexical resources regarding the specificity of word
Using these data and other lexical resources, we will perform a series of quantitative and qualitative analyses in order to explain how word specificity (and related conceptual categories) interacts with concreteness in the following domains:
ABSTRACTION will explain how the specificity and concreteness of words allow us to construct meaning from experience and achieve those generalizations on which much of our thinking and speaking is based. This topic is particularly debated in cognitive science, regarding the "grounding" of abstract concepts, and in artificial intelligence research, where it is still unclear how a machine or algorithm can construct and use concepts and meanings in a way that mirrors human behavior.