Users' view of personalized online news: A study on algorithmic media awareness

In today's world, artificial intelligence and algorithms are widely used in many fields, including communication technologies. In the Internet environment, personalization algorithms use filtering systems defined as content-based similarity, collaborative similarity, content-based diversity to recommend content that may be of interest to users in a large data pool and alleviate the problem of information overload. However, these filtering systems also cause ethical problems such as lack of transparency, biased content, and violations of personal data. Therefore, awareness of personalization algorithms has become a necessity in the digital age. In this study, it was tried to analyze users' awareness levels of algorithms on social media, news application platforms, news websites, etc., and their attitudes towards algorithmic journalism and personalized news recommendation systems. The study, which used quantitative research method and survey technique, was carried out with the participation of 1221 students studying at Selçuk University, Necmettin Erbakan University, Konya Technical University, KTO Karatay University and Konya Food and Agriculture University in Konya province. According to the data obtained from the study, university students' awareness of algorithmic media content and similarity-based news recommendation systems is above the medium level. In the online news reading process, participants are more aware of similarity-based recommendation systems than diversity-based recommendation systems. There is a positive relationship between students' awareness of algorithmic media content and their motivation to use social media, their opinions on algorithmic journalism-based news and their attitudes towards news recommendation systems