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D Gamermann

Biographic Data

ID5854893
NAMED Gamermann
GIVEN NAMESD
FAMILY NAMEGamermann
SIGNATUREGAMERMANN D
AFFILIATIONSUniversidade Federal do Rio Grande do Sul
ORCID0000-0002-3492-264X
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS3
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2013
LATEST PUBLICATION YEAR2018
H-INDEX1
  • Just Google It

    Carmen Moret-Tatay, D Gamermann et al.•ARTICLE•The Journal of General Psychology•2018•Cited by: 1

    Word frequency is one of the most robust factors in the literature on word processing, based on the lexical corpus of a language. However, different sources might be used in order to determine the actual frequency of each word. Recent research has determined frequencies based on movie subtitles, Twitter, blog posts, or newspapers. In this paper, we examine a determination of these frequencies based on the World Wide Web. For this purpose, a Pytho…

  • Differences Between Young and Old University Students on a Lexical Decision Task

    Esperanza Navarro-Pardo, Esperanza Navarro‐Pardo et al.•ARTICLE•The Journal of General Psychology•2013•Cited by: 2•References: 1

    This work compared two common variants of a lexical decision task (LDT) through two different analysis procedures: first, the classical ANOVA method, and second, by fitting the data to an ex-Gaussian distribution function. Two groups of participants (old and young university students) had to perform, blocks of go/no-go and yes/no tasks. Reaction times and error rates were much lower in the go/no-go task than in the yes/no task. Changes in the ex-…

  • Differences Between Young and Old University Students on a Lexical Decision Task

    Esperanza Navarro-Pardo, Esperanza Navarro‐Pardo et al.•ARTICLE•The Journal of General Psychology•2013•Cited by: 2•References: 1

    This work compared two common variants of a lexical decision task (LDT) through two different analysis procedures: first, the classical ANOVA method, and second, by fitting the data to an ex-Gaussian distribution function. Two groups of participants (old and young university students) had to perform, blocks of go/no-go and yes/no tasks. Reaction times and error rates were much lower in the go/no-go task than in the yes/no task. Changes in the ex-…

  • Just Google It

    Carmen Moret-Tatay, D Gamermann et al.•ARTICLE•The Journal of General Psychology•2018•Cited by: 1

    Word frequency is one of the most robust factors in the literature on word processing, based on the lexical corpus of a language. However, different sources might be used in order to determine the actual frequency of each word. Recent research has determined frequencies based on movie subtitles, Twitter, blog posts, or newspapers. In this paper, we examine a determination of these frequencies based on the World Wide Web. For this purpose, a Pytho…

  • Differences Between Young and Old University Students on a Lexical Decision Task

    Esperanza Navarro-Pardo, Esperanza Navarro‐Pardo et al.•ARTICLE•The Journal of General Psychology•2013•Cited by: 2•References: 1

    This work compared two common variants of a lexical decision task (LDT) through two different analysis procedures: first, the classical ANOVA method, and second, by fitting the data to an ex-Gaussian distribution function. Two groups of participants (old and young university students) had to perform, blocks of go/no-go and yes/no tasks. Reaction times and error rates were much lower in the go/no-go task than in the yes/no task. Changes in the ex-…

  • Just Google It

    Carmen Moret-Tatay, D Gamermann et al.•ARTICLE•The Journal of General Psychology•2018•Cited by: 1

    Word frequency is one of the most robust factors in the literature on word processing, based on the lexical corpus of a language. However, different sources might be used in order to determine the actual frequency of each word. Recent research has determined frequencies based on movie subtitles, Twitter, blog posts, or newspapers. In this paper, we examine a determination of these frequencies based on the World Wide Web. For this purpose, a Pytho…

Artificial Intelligence (2 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Lexical decision task (2 works) · Natural language processing (2 works) · Psychology (2 works) · Speech recognition (2 works) · Word (group theory (2 works) · Advanced Text Analysis Techniques (1 work) · Advertising (1 work)

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