Distribute and Be Damned 59
Excite which aimed to become the personalised front page of the web
for the increasing number of users, aggregating content from multiple
sources including news that would be offered via customised feeds. Facebook’s particular refinement (which effectively demolished competitors)
was to combine news sources from more official sources with high personal ones from friends and family. The results were controversial even
in 2014: a number of reports, such as one from The Guardian in June
of that year, reported that Facebook had contravened ethical guidelines
in seeking to manipulate users’ emotions when it conducted experiments
in 2012, hiding a number of emotive words from approximately 1 in
2,500 users without their consent to see whether it would affect their
behaviour on the site.
73
Although the company claimed to be much more open about such
experiments by the time that the News Feed was in full flow, suspicions
continued to linger, and in the next chapter, we shall consider the implications of the Cambridge Analytica scandal and how Facebook was
monetising user information. In his book The Filter Bubble, Eli Pariser
discussed how companies such as Facebook and Google were more
effectively reflecting user’s interests and reinforcing their prejudices,
demonstrating its origins in attempts to collaboratively filter the flood of
information that was starting to emerge in the digital domain as early as
the late 1980s.
74
In many respects, the filter bubble is simply an update
of older concepts of echo chambers or experiments into confirmation
bias conducted by Peter Wason in the 1960s. What made the Facebook
News Feed so effective was that it brought together information from
official or semi-official sources alongside stories from friends and family.
Alongside cat videos or photos of your best friend’s new daughter, News
Feed would display articles about events in your local town, information
about pages of business, and brands you followed – or news about presidential candidates. All the time, Facebook’s algorithm – the Algorithm,
as Zuckerberg and Facebook evangelists referred to it – selected which
stories appeared in the feed, seeking to make the site as addictive as possible and maintain a constant flow of data to advertisers. None of this is
new to Facebook: the consumer/publisher triangle, whereby publishers
serve content to attract readers, who will then provide an audience for
advertisers, has been a stock element of the publishing industry. What
Facebook was able to do – at least for a short time – was to enable thirdparty sources such as advertisers and news (or fake news) producers to
piggyback on the trust that came from sharing more intimate stories
with relatives and close friends.
The effect of this flattening of relations between third-party sources
and friends was dramatic. By August 2017, according to research by
the Pew Research Center, two-thirds of Americans obtained their news
from social media, with a majority relying on Facebook.
75
And yet, as
Vaidhyanathan has pointed out, in 2017 the organisation conceded that
Excite which aimed to become the personalised front page of the web
for the increasing number of users, aggregating content from multiple
sources including news that would be offered via customised feeds. Facebook’s particular refinement (which effectively demolished competitors)
was to combine news sources from more official sources with high personal ones from friends and family. The results were controversial even
in 2014: a number of reports, such as one from The Guardian in June
of that year, reported that Facebook had contravened ethical guidelines
in seeking to manipulate users’ emotions when it conducted experiments
in 2012, hiding a number of emotive words from approximately 1 in
2,500 users without their consent to see whether it would affect their
behaviour on the site.
73
Although the company claimed to be much more open about such
experiments by the time that the News Feed was in full flow, suspicions
continued to linger, and in the next chapter, we shall consider the implications of the Cambridge Analytica scandal and how Facebook was
monetising user information. In his book The Filter Bubble, Eli Pariser
discussed how companies such as Facebook and Google were more
effectively reflecting user’s interests and reinforcing their prejudices,
demonstrating its origins in attempts to collaboratively filter the flood of
information that was starting to emerge in the digital domain as early as
the late 1980s.
74
In many respects, the filter bubble is simply an update
of older concepts of echo chambers or experiments into confirmation
bias conducted by Peter Wason in the 1960s. What made the Facebook
News Feed so effective was that it brought together information from
official or semi-official sources alongside stories from friends and family.
Alongside cat videos or photos of your best friend’s new daughter, News
Feed would display articles about events in your local town, information
about pages of business, and brands you followed – or news about presidential candidates. All the time, Facebook’s algorithm – the Algorithm,
as Zuckerberg and Facebook evangelists referred to it – selected which
stories appeared in the feed, seeking to make the site as addictive as possible and maintain a constant flow of data to advertisers. None of this is
new to Facebook: the consumer/publisher triangle, whereby publishers
serve content to attract readers, who will then provide an audience for
advertisers, has been a stock element of the publishing industry. What
Facebook was able to do – at least for a short time – was to enable thirdparty sources such as advertisers and news (or fake news) producers to
piggyback on the trust that came from sharing more intimate stories
with relatives and close friends.
The effect of this flattening of relations between third-party sources
and friends was dramatic. By August 2017, according to research by
the Pew Research Center, two-thirds of Americans obtained their news
from social media, with a majority relying on Facebook.
75
And yet, as
Vaidhyanathan has pointed out, in 2017 the organisation conceded that