Are Filter Bubbles Real? by Axel Bruns;

Author:Axel Bruns;
Language: eng
Format: epub
ISBN: 9781509536467
Publisher: John Wiley & Sons, Inc.
Published: 2019-09-11T00:00:00+00:00

Although much recent research investigates social media, older notions of filter bubbles as resulting from search and personalisation algorithms have also been challenged. Haim et al. (2018) tested Google News by establishing a small number of fake user profiles with different thematic interests, expressed both explicitly through personalisation settings and implicitly through simulated search and browsing histories; after initial training they used each profile to query identical terms and assessed differences in search results. The study found minor or no effects on the diversity of content and sources in search results (Haim et al. 2018: 339).

Exploring similar questions, Nechushtai and Lewis (2019) asked some 168 real users of varying political interest, ideology and geographic location across the United States to search Google News for the major candidates during the 2016 US presidential election; they, too, found only limited evidence of search result personalisation and ‘neither ideological bias nor geographic bias’ regardless of user demographics (2019: 301). Indeed, one concern they raise is not that Google News search results are so divergent that they create distinct and isolated Republican and Democrat filter bubbles, but rather that they are so similar that they lack ideological variety, creating a single national information cocoon, centred on five major news outlets, that encapsulates almost all Americans – ‘despite the platform’s algorithmic capability of constructing a much more diverse and/or tailored news experience’ (Nechushtai and Lewis 2019: 302).

Google News mainly appears to perpetuate long-established positions of market dominance inherited from a pre-digital era (Nechushtai and Lewis 2019: 302), and the researchers come close to suggesting that a greater level of personalisation and diversity in search results may be desirable. Unexpectedly, like the German Facebook study, these findings almost point to the reemergence of a unified public sphere, thought to have been fragmented beyond repair by cable TV and the World Wide Web – though we must remember that Google News is not the only news aggregator available to those who predominantly seek news through online channels.

This significant concentration of search results on a handful of sources closely matches the highly concentrated patterns of news consumption from ‘a small number of relatively centrist sites’ that Gentzkow and Shapiro found for US online news consumers in an earlier study (2011: 1801). Do search results observed in 2016 exhibit limited variety because search engine algorithms have learnt to cater to largely centrist user preferences established previously, or do the preferences observed in 2011 already result from Google’s algorithmic prioritisation of mainstream news? Perhaps user selections and algorithmic shaping co-evolved together into a feedback loop that reinforces the privileged position of centrist news. Either way, these studies show no evidence of ideological segregation; in Gentzkow and Shapiro’s study, the more ‘ideologically extreme’ sites accounted ‘for a very small share of online consumption’ (2011: 1802).

Finally, a third study of both Google News and Google Search recommendations, conducted by Algorithm Watch ahead of the 2017 German federal election (Krafft et al. 2018), harvested data from over 1,500 volunteers who installed a browser plugin that regularly searched both sites for a fixed list of political leaders and parties.

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