The datafication of student information on X (Twitter)

Abstract

The sharing of personally identifiable information (PII) through social media platforms poses known risks to children's online privacy and safety. While the risks of oversharing PII through a range of digital contexts are becoming better understood, limited research has documented the social media practices of educational institutions that have a fiduciary responsibility to children. This study seeks to understand the role of educational institutions in putting students’ privacy at risk by investigating their social media practices on X (formerly Twitter). This paper extends previous research (Rosenberg et al., 2022a) by exploring how often students' PII (e.g., names, images, and phone numbers) and other social identities (e.g., gender identity, religion, race, and ethnicity) are exposed on X. Additionally, we examine both images and videos of posts shared by educational institutions. Using a data set of approximately 20.6 million posts made by K-12 education institutions in the United States, we explore the extent to which students’ PII is shared with the public on X. Our analyses suggest that approximately 4 % of posts that contain images and videos (approximately 800,000 posts in the overall data set) included an identifiable face of a student or students along with their name(s) and 2.3 % ascribed students’ gender identity. Given the extent of disclosed PII and the potential privacy risks, this study provides additional insight for educational stakeholders to cultivate safer social media practices, seeking to mitigate potential risks to students' privacy and improve students’ digital rights.

Keywords

• Data science applications in education
• Information literacy
• Social media
• Media in education
• Human-computer interface