Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/57403
Title: The internet usage rate in Turkey: a machine learning approach
Authors: İncekara, Mustafa
Öztürk, Cemal
Keywords: Internet Usage Rate
Socio-Economic Factors
Turkey
Machine Learning.
Telephone Surveys
Web Surveys
Coverage
Error
Nonresponse
Methodology
Bias
Publisher: Ege Univ, Fac Economics & Admin Sciences
Abstract: Most studies on measuring coverage bias in internet surveys use internet access as a critical measurement variable. However, access to the internet does not mean that individuals are using it. Therefore, using the internet usage rate as a key variable is crucial to get an accurate overview of the internet coverage of a population. This study closes these gaps by using a better indicator for measuring the internet usage rate. It is the first study measuring the internet usage rate in Turkey by using the real internet usage rate of the population and applying a machine learning algorithm. The results exposed significant differences in socio-demographic characteristics when internet users were compared with non-users. Furthermore, the coverage bias associated with internet users remained different for several demographic categories. The results of web-based surveys based on the actual internet usage rate are crucial for the scientific community and marketers.
URI: https://doi.org/10.21121/eab.1268873
https://hdl.handle.net/11499/57403
ISSN: 1303-099X
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record



CORE Recommender

Page view(s)

26
checked on Aug 24, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.