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Hits 1 – 3 of 3
1
Word Embeddings Reveal How Fundamental Sentiments Structure Natural Language ...
van Loon, Austin
;
Freese, Jeremy
. - : SAGE Journals, 2022
Abstract:
Central to affect control theory are culturally shared meanings of concepts. That these sentiments overlap among members of a culture presumably reflects their roots in the language use that members observe. Yet, the degree to which the affective meaning of a concept is encoded in the way linguistic representations of that concept are used in everyday symbolic exchange has yet to be demonstrated. The question has methodological as well as theoretical significance for affect control theory, as language may provide an unobtrusive, behavioral method of obtaining EPA ratings complementary to those heretofore obtained via questionnaires. We pursue a series of studies that evaluate whether tools from machine learning and computational linguistics can capture the fundamental affective meaning of concepts from large text corpora. We develop an algorithm that uses word embeddings to predict EPA profiles available from a recent EPA dictionary derived from traditional questionnaires, as well as novel concepts collected ...
Keyword:
170199 Psychology not elsewhere classified
;
FOS Psychology
;
FOS Sociology
;
Sociology
URL:
https://dx.doi.org/10.25384/sage.c.5860085
https://sage.figshare.com/collections/Word_Embeddings_Reveal_How_Fundamental_Sentiments_Structure_Natural_Language/5860085
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2
Word Embeddings Reveal How Fundamental Sentiments Structure Natural Language ...
van Loon, Austin
;
Freese, Jeremy
. - : SAGE Journals, 2022
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3
Regional Negative Bias in Word Embeddings Predicts Racial Animus--but only via Name Frequency ...
van Loon, Austin
;
Giorgi, Salvatore
;
Willer, Robb
. - : arXiv, 2022
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