Algorithms are a ubiquitous part of the internet, which customise the selection and presentation of web content to the user based on various factors in the process known as algorithmic curation. Algorithms operate by using data that users (in)directly share online. Algorithms' ubiquity, therefore, highlights the importance of algorithmic literacy, which refers to the user's understanding of algorithms and enables them to navigate competently online. The algorithms' functioning based on data and their accessibility to (unknown) third parties has led to the need for online privacy literacy, which refers to the user's knowledge of online data protection and gives them more control over their own data. There seem to be several conceptual and practical connections between the two literacies, but their relationship has not yet been directly studied. Therefore, in this master's thesis, we were interested in how they are related to their dimensions of theoretical constructs on a conceptual and empirical level. To this end, we set a research question and four working hypotheses, where we compare the strength of the connection between their dimensions. We conducted a web survey among social network users and, by means of bivariate analyses, checked the empirical validity of the hypotheses. To measure both literacies, we used the Algorithmic Literacy Scale and the Online Privacy Literacy Scale. The results confirmed three out of four hypotheses. Our findings provide an important contribution to the understanding of mechanisms that shape the relationship between the two literacies on the individual and societal level.
|
