Data Analysis of European Union states: youth behavior in digital world

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F18%3A39913211" target="_blank" >RIV/00216275:25410/18:39913211 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Data Analysis of European Union states: youth behavior in digital world

Popis výsledku v původním jazyce

The paper deals with data analysis of young people behaviour (in age from 16 to 29 years) in digital world living in the European Union States. For this analysis, ten selected indicators from the area of digital world (focused for example on working with Internet, on social networks, on the Internet banking, on searching of information about travelling, about goods and services, e-mail communication and calls) and two economic indicators (gross domestic product per capita and unemployment rate) were chosen. Derived attributes were calculated in the data pre-processing phase. Selected algorithms of the agglomerative hierarchical clustering (as are the nearest neighbour method, the furthest neighbour method, the centroid clustering, the median clustering and the Ward method etc.) were used to find groups of similar objects (individual states of the European Union) based on the chosen indicators. Values of average coefficients of growth were used for clustering. The best results of clustering were achieved by the Ward‘s method; the data was divided into three clusters. Identified groups of European Union States were described by mentioned indicators.

Název v anglickém jazyce

Data Analysis of European Union states: youth behavior in digital world

Popis výsledku anglicky

The paper deals with data analysis of young people behaviour (in age from 16 to 29 years) in digital world living in the European Union States. For this analysis, ten selected indicators from the area of digital world (focused for example on working with Internet, on social networks, on the Internet banking, on searching of information about travelling, about goods and services, e-mail communication and calls) and two economic indicators (gross domestic product per capita and unemployment rate) were chosen. Derived attributes were calculated in the data pre-processing phase. Selected algorithms of the agglomerative hierarchical clustering (as are the nearest neighbour method, the furthest neighbour method, the centroid clustering, the median clustering and the Ward method etc.) were used to find groups of similar objects (individual states of the European Union) based on the chosen indicators. Values of average coefficients of growth were used for clustering. The best results of clustering were achieved by the Ward‘s method; the data was divided into three clusters. Identified groups of European Union States were described by mentioned indicators.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific Papers of the University of Pardubice - Series D, Faculty of Economics and Administration

ISSN

1211-555X

e-ISSN

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Svazek periodika

26

Číslo periodika v rámci svazku

44

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

12

Strana od-do

102-113

Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-85065592136