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Guillermo Jorge-Botana

Biographic Data

ID5019773
NAMEGuillermo Jorge-Botana
GIVEN NAMESGuillermo
FAMILY NAMEJorge-Botana
SIGNATUREJORGE-BOTANA G
AFFILIATIONSUniversidad Complutense de Madrid
VERIFIEDNo
TOTAL WORKS3
TOTAL CITATIONS2
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2014
LATEST PUBLICATION YEAR2025
H-INDEX1
  • Are valence and arousal related to the development of amodal representations of words? A computational study

    José Ángel Martínez-Huertas, José Ángel Martínez‐Huertas et al.•ARTICLE•Cognition & Emotion•2025•Cited by: 1•References: 23

    In this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at d…

  • Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

    Guillermo Jorge-Botana, Guillermo Jorge‐Botana et al.•ARTICLE•Discourse Processes•2017•Cited by: 1•References: 34

    Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of a word at every age is then compared with its adult representation via computational maturity indice…

  • Transforming Selected Concepts Into Dimensions in Latent Semantic Analysis

    Ricardo Olmos, Guillermo Jorge-Botana et al.•ARTICLE•Discourse Processes•2014•References: 17

    This study presents a new approach for transforming the latent representation derived from a Latent Semantic Analysis (LSA) space into one where dimensions have nonlatent meanings. These meanings are based on lexical descriptors, which are selected by the LSA user. The authors present three analyses that provide examples of the utility of this methodology. The first analysis demonstrates how document terms can be projected into meaningful new dim…

  • Are valence and arousal related to the development of amodal representations of words? A computational study

    José Ángel Martínez-Huertas, José Ángel Martínez‐Huertas et al.•ARTICLE•Cognition & Emotion•2025•Cited by: 1•References: 23

    In this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at d…

  • Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

    Guillermo Jorge-Botana, Guillermo Jorge‐Botana et al.•ARTICLE•Discourse Processes•2017•Cited by: 1•References: 34

    Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of a word at every age is then compared with its adult representation via computational maturity indice…

  • Transforming Selected Concepts Into Dimensions in Latent Semantic Analysis

    Ricardo Olmos, Guillermo Jorge-Botana et al.•ARTICLE•Discourse Processes•2014•References: 17

    This study presents a new approach for transforming the latent representation derived from a Latent Semantic Analysis (LSA) space into one where dimensions have nonlatent meanings. These meanings are based on lexical descriptors, which are selected by the LSA user. The authors present three analyses that provide examples of the utility of this methodology. The first analysis demonstrates how document terms can be projected into meaningful new dim…

  • Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

    Guillermo Jorge-Botana, Guillermo Jorge‐Botana et al.•ARTICLE•Discourse Processes•2017•Cited by: 1•References: 34

    Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of a word at every age is then compared with its adult representation via computational maturity indice…

  • Are valence and arousal related to the development of amodal representations of words? A computational study

    José Ángel Martínez-Huertas, José Ángel Martínez‐Huertas et al.•ARTICLE•Cognition & Emotion•2025•Cited by: 1•References: 23

    In this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at d…

Artificial Intelligence (2 works) · Computer Science (2 works) · Latent semantic analysis (2 works) · Mathematics (2 works) · Natural language processing (2 works) · Natural Language Processing Techniques (2 works) · Psychology (2 works) · Representation (politics (2 works) · Topic Modeling (2 works) · Advanced Text Analysis Techniques (1 works)

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