Artículos de revistas
The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text
Fecha
2017-11Registro en:
Altszyler Lemcovich, Edgar Jaim; Ribeiro, Sidarta; Sigman, Mariano; Fernandez Slezak, Diego; The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text; Elsevier; Consciousness and Cognition; 56; 11-2017; 178-187
1053-8100
CONICET Digital
CONICET
Autor
Altszyler Lemcovich, Edgar Jaim
Ribeiro, Sidarta
Sigman, Mariano
Fernandez Slezak, Diego
Resumen
Computer-based dreams content analysis relies on word frequencies within predefined categories in order to identify different elements in text. As a complementary approach, we explored the capabilities and limitations of word-embedding techniques to identify word usage patterns among dream reports. These tools allow us to quantify words associations in text and to identify the meaning of target words. Word-embeddings have been extensively studied in large datasets, but only a few studies analyze semantic representations in small corpora. To fill this gap, we compared Skip-gram and Latent Semantic Analysis (LSA) capabilities to extract semantic associations from dream reports. LSA showed better performance than Skip-gram in small size corpora in two tests. Furthermore, LSA captured relevant word associations in dream collection, even in cases with low-frequency words or small numbers of dreams. Word associations in dreams reports can thus be quantified by LSA, which opens new avenues for dream interpretation and decoding.