AI-assisted sentiment analysis of X posts regarding compulsory distance education processes in Turkey

This doctoral study aimed to analyze societal perceptions of distance education, which was mandatorily implemented during unexpected crises such as the COVID-19 pandemic and earthquakes in Turkey, through social media posts on the X platform. Posts on X were analyzed using sentiment analysis, examining both positive and negative sentiments toward distance education. This study focuses on key periods, including the closure of schools and the launch of distance education in 2020, the full lockdown and transition back to face-to-face education in 2021, and the reimplementation of distance education following the Kahramanmaraş-centered earthquake in 2023. The primary drivers of negative sentiments include lack of social interaction, inadequate technical infrastructure, and accessibility issues. These findings are evaluated within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT), which explains technology acceptance. This study highlights the need to strengthen technical infrastructure, enhance social interaction, and expand individualized learning opportunities to improve the effectiveness of distance education during crises. Furthermore, it demonstrates that big data-driven social media analysis can serve as a valuable methodological tool in educational research.