how does news infomediation operate: the examples of google and facebook
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How does news infomediation operate online?
The examples of Google and Facebook
Nikos SmyrnaiosUniversity of Toulouse
10th World Media Economics & Management Conference, Thessaloniki May 2012
Research question & method
What are the socio-economic stakes of infomediation for online media ?
Research project financed by the French Ministry of Culture and Communication in 2011
4 researchers from France and Canada
Interviews with publishers (Libération, Rue 89, AFP, Radio Canada etc.) & infomediaries (Google, Orange, Wikio, Netvibes etc.), In situ observations
What is an infomediary ?
Infomediaries are information intermediaries
“Permits users to get information meeting their needs” (Jacso, 1988, p.217).
“Connecting information supply with information demand and helping both parties involved determine the value of that
information” (Hagel III, Rayport, 1997, p. 9).
Represent the logical layers of the internet composed of algorithms and software that allow communication between
humans and computers (Benkler, 2006)
Google, Facebook, Apple, Netvibes, Twitter, Flipboard etc.
News infomediation Online news oversupply: ½ million news items per
day produced (Yang, Lescovec, 2011)
Need for filtering, selection, prioritization & matching between news supply and demand
News infomediaries: platforms that operate a mix of edition, aggregation and distribution of third
party news content through links
Based on algorithms and mediatized social interactions, financed by advertising and
marketing
Cooperation & competitionCoopetition = simultaneous cooperation &
competition between publishers & infomediaries (Brousseau, 2001)
Mutual dependency: infomediaries need publishers for their content, publishers need
infomediaries for their trafic
Economic competition: both categories of players engaged in fierce competition for online
advertising revenue
Symbolic competition: who’s rules follow the news ?
Google News
Google News transforms the social logics of news into
algorithms (e.g. agenda setting)
Krishna Bharat’s idea in 2001:
how to satisfy user queries on news efficiently and in
real-time ?
Newsworthiness for Google
For news websites: productiveness, reactivity, popularity, topic spectrum width
For news topics: cluster size, novelty, sources
For news items: novelty, originality, click-through rate, mentions in social media, sources
Conflict and adaptation2003-2008 conflicting period between Google and
publishers in Europe
Lawsuit in Belgium on copyright infringement, conflict in France, Germany, Italy, Denmark, UK
Litigation over “customer information confiscation”
2008-2009 Google changes strategy: deal with AFP, Canadian Press, UKPA & French publishers
In the meantime publishers “enslave themselves to Google”: shovelware, extreme SEO, sponsored
links
Google’s still big for news20-80% of all traffic of news websites (Europe &
US)
Also a major competitor: in 2009 $2,100M advertising revenue in France & Germany for
Google, $500M for all news publishers together
2011 Google’s Panda algorithm wiped out a popular news aggregator in France Wikio among
others
Publishers anti-Google strategies: paywalls, joint portals, distribution through Apple and…
Facebook’s infomediationSocial infomediation =
Platform + users sharing information + Publishers
providing content
2010: Facebook doubles the traffic Google News sends to US publishers
2011: Facebook 3rd traffic provider behind Google. 6% for Nytimes, 8% for HuffPost, 13% for Owni
March 2012: The Guardian gets more traffic from FB than from Google
Social but still algorithmicEdgerank is an automated mechanism to
establish relevancy and visibility in Facebook
Publisher need to master Facebook constraints in order to gain traffic (e.g. community manager)
Like and Share buttons proliferate. Facebook is colonizing news sites & gets usage data
Latest feature: “frictionless sharing”& social readers
Facebook Insights becomes mainstream
How to become indispensable
Publishers make Open Graph applications inside
or outside FB
Users share news automatically with friends
New metrics for publishers: Monthly &
Daily Active Users
Accurate demographics and preferences data
Dangers of dependency
In April 2012 Facebook changed the rules: big drop
1st quarter: Washington Post spent $800,000 in ads
Facebook gets all the data about what people
read & like => “confiscating” marketing revenue
ConclusionsOnline media are highly dependent on
infomediaries
They obey at the rules the infomediaries dictate
Competition results in low cost & redundant content
Infomediaries profit from news value without producing content
Concentration of power & revenue in the hands of a few internet firms
So what about Apple …
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