User behavior and awareness of filter bubbles in social media

Abstract

To counter information overflow, social media companies employ recommender algorithms that potentially lead to filter bubbles. This leaves users’ newsfeed vulnerable to misinformation and might not provide them with a view of the full spectrum of news. There is research on the reaction of users confronted with filter bubbles and tools to avoid them, but it is not much known about the users’ awareness of the phenomenon. We conducted a survey about the usage of Facebook’s newsfeed with 140 participants from Germany and identified two user groups with k-means clustering. One group consisting of passive Facebook users was not very aware of the issue, while users of the other group, mainly heavy professional Facebook users were more aware and more inclined to apply avoidance strategies. Especially users who were aware of filter bubbles wished for a tool to counter them. We recommend targeting users of the first group to increase awareness and find out more about the way professionals use Facebook to assist them countering the filter bubble and promoting tools that help them do so.