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Reaction: Exposure to unreliable or partisan news on Google depends more on user choice than on algorithm

A study led by researchers from Northeastern University and Stanford University in Boston (USA) has analysed the source of exposure to partisan or unreliable news when searching on Google. After tracking the information consumption of approximately 1,000 people in the 2018 and 2020 US election periods, their conclusions are that such exposure is determined more by users' own active search than by the content displayed by the search engine's algorithm. The results are published in the journal Nature.

24/05/2023 - 17:00 CEST
Expert reactions

Walter Quattrociocchi - algoritmo elecciones EN

Walter Quattrociocchi

Director of the Laboratory of Data and Complexity for Society at the University of Rome La Sapienza (Italy)

Science Media Centre Spain

This study is well-designed and adds valuable data to the ongoing conversation about the role of online platforms in societal polarization. 

This study builds upon existing literature by focusing on user behavior and choices on Google Search, a platform often overlooked in favor of social media platforms in this context. The novelty here is examining exposure and engagement during two key periods, the 2018 and 2020 US elections. 

The study does not challenge the notion of online echo chambers by finding that user choice drives engagement with partisan and unreliable news sources more than algorithmic curation. Echo chambers are an emerging effect of confirmation bias (in agreement with the study), algorithmic selection (the business model of platforms proposes content to maximize the permanence of the users on the system), and information overload. So I would not say that a study not using social media platforms is challenging something happening on social media platforms. 

While the study is well-structured and offers intriguing insights, it does have some limitations. It focuses on Google Search and does not extend its findings to other platforms like Twitter, Facebook, or WhatsApp. User behavior and algorithmic influence may vary greatly across these different platforms, so we must be cautious in extrapolating the findings. 

Additionally, the study covers the 2018 and 2020 US elections - periods of high political engagement. It would be interesting to explore whether the trends observed persist during non-election periods.  

This study raises important questions about user autonomy and digital literacy in the context of online news consumption. The challenge for the future will be to navigate the fine balance between user choice and algorithmic guidance to safeguard the quality of online information. 

The author has not responded to our request to declare conflicts of interest
Users choose to engage with more partisan news than they are exposed to on Google Search
  • Research article
  • Peer reviewed
  • Observational study
  • People
Publication date

Robertson et al.

Study types:
  • Research article
  • Peer reviewed
  • Observational study
  • People
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