Analysis of Mobile Social Networks Using Clustering
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F16%3A39900899" target="_blank" >RIV/00216275:25530/16:39900899 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1166/as1.2016.6688" target="_blank" >http://dx.doi.org/10.1166/as1.2016.6688</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1166/as1.2016.6688" target="_blank" >10.1166/as1.2016.6688</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Analysis of Mobile Social Networks Using Clustering
Popis výsledku v původním jazyce
Social networks are becoming a phenomenon of the 21st century. As well as gaining new users on the Internet, they also began to penetrate into mobile devices. The aim of the paper is to introduce the five most commonly used mobile social networks in Europe, with a focus on the European Union and their analysis. For this purpose, the data-mining technology of K-means for clustering process will be used. Prior to the cluster analysis itself, the data will be illustrated using principal component method for graphical visualization, which will define the three main components. The factors according to which there is a clustering, will be detected by a factor analysis using "varimax simple" rotation. In the last part of the paper, the 28 European Union countries are divided into four homogeneous groups, i.e. clusters, for each of the years 2010-2014. These are average values representing the states contained in the given cluster, in comparison with data for all social networks for the European Union and Europe. The input assumption that data (criteria) that enter the cluster analysis are not affected by multi-collinearity, will be verified by Spearman correlation coefficient.
Název v anglickém jazyce
Analysis of Mobile Social Networks Using Clustering
Popis výsledku anglicky
Social networks are becoming a phenomenon of the 21st century. As well as gaining new users on the Internet, they also began to penetrate into mobile devices. The aim of the paper is to introduce the five most commonly used mobile social networks in Europe, with a focus on the European Union and their analysis. For this purpose, the data-mining technology of K-means for clustering process will be used. Prior to the cluster analysis itself, the data will be illustrated using principal component method for graphical visualization, which will define the three main components. The factors according to which there is a clustering, will be detected by a factor analysis using "varimax simple" rotation. In the last part of the paper, the 28 European Union countries are divided into four homogeneous groups, i.e. clusters, for each of the years 2010-2014. These are average values representing the states contained in the given cluster, in comparison with data for all social networks for the European Union and Europe. The input assumption that data (criteria) that enter the cluster analysis are not affected by multi-collinearity, will be verified by Spearman correlation coefficient.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
BB - Aplikovaná statistika, operační výzkum
OECD FORD obor
—
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Advanced Science Letters
ISBN
—
ISSN
1936-6612
e-ISSN
—
Počet stran výsledku
5
Strana od-do
1273-1277
Název nakladatele
American Scientific Publishers
Místo vydání
Valencia
Místo konání akce
Bali
Datum konání akce
29. 9. 2015
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000383113900041