Naslov
Using clustering methods to identify different profiles based on similarity in online security and privacy attitudes

Autori
Peras, Dijana ; Mekovec, Renata

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
ICIEB 2021 Conference Proceedings / Cartana Alvaro, Xavier ; Cellary, Wojciech - Barcelona : The Association for Computing Machinery (ACM), 2021, 9-14

ISBN
978-1-4503-9021-7

Skup
2nd International Conference on Internet and E-Business

Mjesto i datum
Barcelona, Španjolska, 09.06.2021. - 11.06.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Online privacy, EU countries, K-means clustering

Sažetak
This paper examines behavior patterns related to online security and privacy attitudes from individuals across 28 European Union (EU) countries. By using the k-means clustering, the countries were assigned to three different profiles based on similarities in online security and privacy attitudes. The study revealed significant differences in online security and privacy attitudes between individuals from countries assigned to high, low and medium concerned profile. Concerns about online privacy and security of individuals in high concern profile were significantly higher compared to other two profiles, while individuals in low concern profile expressed a significantly lower level of concern about online privacy and security compared to other two profiles. A cross- national EU-based exploration and visual mapping of attitudes was provided

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA