Reliance on social media as a source of information has lead to several challenges, including the limitation of sources to viewers’ preferences and desires, also known as filter bubbles. The formation of filter bubbles is a known risk to democracy. It can bring negative consequences like polarisation of the society, users’ tendency to extremist viewpoints and the proliferation of fake news. Previous studies have focused on specific aspects and paid less attention to a holistic approach for eliminating the notion. The current study, however, aims to propose a model for an integrated tool that assists users in avoiding filter bubbles in social networks. To this end, a systematic literature review has been undertaken, and initially, 571 papers in six top-ranked scientific databases have been identified. After excluding irrelevant studies and performing an in-depth analysis of the remaining papers, a classification of research studies is proposed. This classification is then used to introduce an overall architecture for an integrated tool that synthesises all previous studies and offers new features for avoiding filter bubbles. The study explains the components and features of the proposed architecture and concludes with a list of implications for the recommended tool.
|Number of pages||16|
|Journal||Australasian Journal of Information Systems|
|Publication status||Published - 6 Apr 2021|
Bibliographical noteCopyright (c) 2021 Alireza Amrollahi. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
- filter bubble
- social networks
- prescriptive study
- information bubble