The question of whether a social media platform promotes connections with accounts that engage in unwanted surveillance raises significant privacy concerns. This involves an examination of the platform’s algorithms and their potential to suggest profiles to users based on data indicative of stalking behavior, whether intentional or unintentional. For instance, if a user repeatedly views another user’s profile, even without direct interaction, does the platform interpret this as a signal to recommend that targeted profile?
Understanding the mechanisms behind user suggestions on social media is vital for promoting online safety and protecting individuals from potential harassment. Social platforms often prioritize engagement metrics, such as profile views and content interactions, to determine which connections to recommend. A historical context reveals that early social media platforms focused primarily on connecting existing acquaintances, while contemporary platforms increasingly employ algorithms to suggest connections based on broader patterns of activity and inferred interests, potentially blurring the lines between desired connection and unwanted attention.
