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