1. How does news infomediation
operate online?
The examples of Google and Facebook
Nikos Smyrnaios
University of Toulouse
10th World Media Economics & Management Conference, Thessaloniki May 2012

2. 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

3. 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.

4. 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

5. Cooperation & competition
Coopetition = 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 ?

6. Google News
Krishna Bharat’s idea
in 2001:
how to satisfy user
queries on news
efficiently and in real-
time ?
Google News
transforms the social
logics of news into
algorithms
(e.g. agenda setting)

7. 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

8. Conflict and adaptation
2003-2008 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

9. Google’s still big for news
20-80% 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…

10. Facebook’s infomediation
Social 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

11. Social but still algorithmic
Edgerank 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

12. 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

13. 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

14. Conclusions
Online 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 …