Investigating the effect of artificial intelligence on content productivity in social media

The purpose of this study is to examine university students' attitudes and opinions regarding artificial intelligence-supported content production processes in social media environments. In the study, a transformative mixed-methods design was used, which combines quantitative and qualitative data collection approaches. The data collection tools used were a survey on the impact of artificial intelligence on content productivity and a semi-structured interview form. The study population consists of undergraduate students enrolled in media literacy courses at state universities in Turkey during the spring semester of the 2024–2025 academic year. Within the scope of the research, quantitative data was collected through a survey on the effect of artificial intelligence on content productivity administered to 76 students, while qualitative data was collected through semi-structured interviews with 10 students. The quantitative data of the research was analyzed using IBM SPSS Statistics 30.0 software. An independent samples t-test analysis was applied to determine the difference between the pre- and post-course groups' survey scores. The qualitative data obtained in the qualitative analysis process of this study were analyzed using the thematic analysis method. The study's dataset was created because of semi-structured interviews conducted with 10 university students taking a media literacy course. According to the data findings, students' attitudes toward the use of artificial intelligence in the content creation process on social media were found to be positive. The study revealed that attitudes toward artificial intelligence can be developed, structured educational programs are effective in this regard, and demographic variables predict this effect to a limited extent. Keywords: Artificial intelligence, social media, content creation, media literacy