From Indiana University:
Indiana University researchers have found that people who seek out news and information from social media are at higher risk of becoming trapped in a “collective social bubble” compared to using search engines.
The study, “Measuring online social bubbles,” was recently published in the open-access online journal PeerJ Computer Science. The results are based on an analysis of over 100 million Web clicks and 1.3 billion public posts on social media.
“These findings provide the first large-scale empirical comparison between the diversity of information sources reached through different types of online activity,” said Dimitar Nikolov, a doctoral student in the School of Informatics and Computing at IU Bloomington, who is lead author on the study. “Our analysis shows that people collectively access information from a significantly narrower range of sources on social media compared to search engines.”
Overall, the analysis found that people who accessed news on social media scored significantly lower in terms of the diversity of their information sources than users who accessed current information using search engines.
The results show the rise of a “collective social bubble” where news is shared within communities of like-minded individuals, said Nikolov, noting a trend in modern media consumption where “the discovery of information is being transformed from an individual to a social endeavor.”
He added that people who adopt this behavior as a coping mechanism for “information overload” may not even be aware they’re filtering their access to information by using social media platforms, such as Facebook, where the majority of news stories originate from friends’ postings.
Read the Indiana University News Article
Direct to Full Text Article Discussed in the Article: Measuring online social bubbles (via PeerJ)
From the Abstract:
Social media have become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view. Here we quantitatively measure this kind of social bias at the collective level by mining a massive datasets of web clicks. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to a search baseline. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at both the collective and individual levels in two datasets where individual users can be analyzed—Twitter posts and search logs. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside “social bubbles.” Our results could lead to a deeper understanding of how technology biases our exposure to new information.