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How does news infomediation operate: the examples of Google and Facebook

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How does news infomediation operate: the examples of Google and Facebook

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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 …

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