Abstract
More and more often companies use algorithms to provide highly personalized and targeted recommendations to online users. Usually, algorithms find those recommendations by analyzing past (shopping) behavior. However, this past-oriented approach has not been uncriticized as it leads to a so-called filter bubble. This article sheds light to the filter bubble focusing on users’ perception and reaction. In an online survey 120 Facebook users have been asked about their newsfeeds. The results show that persons intensively using social media perceive the filter bubble more often than those sporadically using social media in their daily life. Moreover, the education level as well as the interaction between relevance and intensity of Facebook usage have a significant influence on the filter bubble perception. The perception itself influences the attitude towards the filter bubble. However, in our model no significant relation has been found between attitudes towards the filter bubble and behavioral reaction. Finally, implications are deviated.
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Klug, K., Strang, C. (2019). The Filter Bubble in Social Media Communication: How Users Evaluate Personalized Information in the Facebook Newsfeed. In: Osburg, T., Heinecke, S. (eds) Media Trust in a Digital World. Springer, Cham. https://doi.org/10.1007/978-3-030-30774-5_12
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