Abstract:
Since the introduction of smartphones and applications, privacy concerns have been rapidly rising. Today, over one billion people use smartphones with millions of apps. These apps may request different permissions from users. Whether it’s Android, IOS, Windows, or any other mobile operating system, apps may mostly request permissions more than necessary. In this study, Android apps from Google Play Store are examined. Python scraping code was used to collect details for over 5,000 apps including different parameters such as permissions requested and number of installs. The data was then analyzed using SPSS, AMOS, and Power BI. The analyses made varied from simple descriptive, to one-way ANOVA, multiple regression, and correlation. Also, graphs were constructed. Data analysis was fruitful and different hypothesis were significantly. The results showed that number of permissions requested is correlated with several other variables such as number of reviews, number of installs, and review score. Also, ANOVA tests showed that different developers and categories can possess statistically different number of permissions requested. The study has several limitations such as the IP address of the computer used in Turkey. Turkish apps were suggested. Also, the number of apps collected was 5,264 which relative to total number of apps on the store might be considered as small and non-representative.
