Dataset Information

Semantic network from the words happiness and wellbeing: Dataset in a Mexican sample.

ABSTRACT: The present paper presents data with information about related words for happiness and wellbeing attributed by people living in a northern city of Mexico. Quota sampling technique was used to collect the data following the distribution of the population by age and gender. National Institute of Geography and Statistics in México was consulted to obtain the proportion of age range and gender in the city of Guaymas, Sonora. Participants from 18 to 85 years old (M = 41.77, ST = 16.76) answer the instrument for a semantic network technique, which is composed by two steps, first freely answer words related to each concept (happiness/wellbeing), and second, hierarchizing them from the most to the least related. The dataset presents the words given by the participants ordered by their hierarchy; number one indicates the concept that people indicated as the most related to the concept. This article presents the ten more related words for each concept (Table 1), the ten related words by male and female for wellbeing (Table 2), and happiness (Table 3). Health is more related to wellbeing, while the family is more frequently related to happiness.

SUBMITTER: Duron-Ramos MF

PROVIDER: S-EPMC6889765 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Semantic network from the words happiness and wellbeing: Dataset in a Mexican sample.

Durón-Ramos Maria F MF García-Vazquez Fernanda I FI Castellanos Luis M LM

Data in brief 20191116

The present paper presents data with information about related words for happiness and wellbeing attributed by people living in a northern city of Mexico. Quota sampling technique was used to collect the data following the distribution of the population by age and gender. National Institute of Geography and Statistics in México was consulted to obtain the proportion of age range and gender in the city of Guaymas, Sonora. Participants from 18 to 85 years old (M = 41.77, ST = 16.76) answer the ins ...[more]

PMID: 31828189

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Project description:Semantic processing of visually presented words can be identified both on behavioral and neurophysiological evidence. One of the major discoveries of the last decades is the demonstration that these signatures of semantic processing, initially observed for consciously perceived words, can also be detected for masked words inaccessible to conscious reports. In this context, the distinction between conscious and unconscious verbal semantic processing constitutes a challenging scientific issue. A prominent view considered that while conscious representations are subject to executive control, unconscious ones would operate automatically in a modular way, independent from control and top-down influences. Recent findings challenged this view by revealing that endogenous attention and task-setting can have a strong influence on unconscious processing. However, one of the major arguments supporting the automaticity of unconscious semantic processing still stands, stemming from a seminal observation reported by Marcel in 1980 about polysemous words. In the present study we reexamined this evidence. We present a combination of behavioral and event-related-potentials (ERPs) results that refute this view by showing that the current conscious semantic context has a major and similar influence on the semantic processing of both visible and masked polysemous words. In a classical lexical decision task, a polysemous word was preceded by a word which defined the current semantic context. Crucially, this context was associated with only one of the two meanings of the polysemous word, and was followed by a word/pseudo-word target. Behavioral and electrophysiological evidence of semantic priming of target words by masked polysemous words was strongly dependent on the conscious context. Moreover, we describe a new type of influence related to the response-code used to answer for target words in the lexical decision task: unconscious semantic priming constrained by the conscious context was present both in behavior and ERPs exclusively when right-handed subjects were instructed to respond to words with their right hand. The strong and respective influences of conscious context and response-code on semantic processing of masked polysemous words demonstrate that unconscious verbal semantic representations are not automatic.

Dataset Information

Semantic network from the words happiness and wellbeing: Dataset in a Mexican sample.

Publications

Semantic network from the words happiness and wellbeing: Dataset in a Mexican sample.

Similar Datasets

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