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The Emotions of Abstract Words: A Distributional Semantic Analysis
Author(s) -
Lenci Alessandro,
Lebani Gianluca E.,
Passaro Lucia C.
Publication year - 2018
Publication title -
topics in cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.191
H-Index - 56
eISSN - 1756-8765
pISSN - 1756-8757
DOI - 10.1111/tops.12335
Subject(s) - embodied cognition , emotive , psychology , representation (politics) , cognitive psychology , set (abstract data type) , linguistics , computer science , artificial intelligence , epistemology , philosophy , politics , political science , law , programming language
Recent psycholinguistic and neuroscientific research has emphasized the crucial role of emotions for abstract words, which would be grounded by affective experience, instead of a sensorimotor one. The hypothesis of affective embodiment has been proposed as an alternative to the idea that abstract words are linguistically coded and that linguistic processing plays a key role in their acquisition and processing. In this paper, we use distributional semantic models to explore the complex interplay between linguistic and affective information in the representation of abstract words. Distributional analyses on Italian norming data show that abstract words have more affective content and tend to co‐occur with contexts with higher emotive values, according to affective statistical indices estimated in terms of distributional similarity with a restricted number of seed words strongly associated with a set of basic emotions. Therefore, the strong affective content of abstract words might just be an indirect byproduct of co‐occurrence statistics. This is consistent with a version of representational pluralism in which concepts that are fully embodied either at the sensorimotor or at the affective level live side‐by‐side with concepts only indirectly embodied via their linguistic associations with other embodied words.