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1

PERSONALITY TRAITS AND THE RISKY USE OF SOCIAL MEDIA IN SLOVAK ADOLESCENTS

100%
Ďuricová L., Poliach V.
Človek a spoločnosť. Internetový časopis pre pôvodné teoretické a výskumné štúdie z oblasti spoločenských vied
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2023
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vol. 26
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issue 1
-
EN
Despite being a pressing issue, the role of personality traits in the adolescent use of social networks has not yet been researched empirically in Slovakia. The aim of this study is to increase knowledge about the relationship between the tendency to overuse social media, personality traits and self-esteem in a sample of Slovak adolescents. Furthermore, it also confirms the gender differences in the tendency of male and female adolescents to use social media in a risky way. The research sample comprised 284 Slovak adolescents aged between 15 and 20 years old (M = 17.88, SD = 1.67); 141 of the subjects were female. The data collection was carried out using the snowball method i.e., by means of a Facebook questionnaire. The study suggests the importance of personality factors such as neuroticism and conscientiousness in explaining the tendency to overuse social media. The role of personality traits and gender differences may be relevant for designing prevention activities and intervention programmes on risky social networking use in adolescence.
2

REGRESSION QUANTILES UNDER HETEROSCEDASTICITY AND MULTICOLLINEARITY: ANALYSIS OF TRAVEL AND TOURISM COMPETITIVENESS

86%
Kalina J., Vašaničová P., Litavcová E.
Ekonomický časopis (Journal of Economics)
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2019
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vol. 67
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issue 1
69 – 85
EN
In the linear regression, heteroscedasticity and multicollinearity can be characterized as intertwined problems, which often simultaneously appear in econometric models. The aim of this paper is to discuss various approaches to regression modelling for heteroscedastic multi collinear data. A real economic dataset from the World Economic Forum serves as an illustration of various individual methods and the paper provides a practical motivation for quantile regression and particularly for regularized regression quantiles. In the dataset, tourist service infrastructure across 141 countries is modelled as a response of 12 characteristics of the Travel and Tourism Competitiveness Index (TTCI). Regression quantiles and their lasso estimates turn out to be more suitable for the dataset compared to more traditional econometric tools.
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