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Crowdsourcing and Markets in the Social Media Age

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Presentation of the crowdsourced geotagging service HP gloe from a research perspective

Presentation of the crowdsourced geotagging service HP gloe from a research perspective

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  • Social attention: detected not inside people’s heads but in their interactions attention not as an individual psychological mechanism, but as a social phenomenon measured by the intensity of signals that relate to a particular idea, theory, product, research program, movie, book, etc.
  • James Surowiecki The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations
  • 1.7 billion Internet users world wide, 380% growth since 2000 (Internet World Stats) Youtube: 100s of millions views/day, 100s of thousands uploads/day, 2007 10% of all internet traffic (Ellacoya networks) 2008: on high speed links, 20% p2p, 50% streaming video (Arbor Networks) Jimmie Wales, wikipedia not crowdsourced (negative connotation of free labor)
  • Robin Hanson, DoD Policy Analysis Market. Prediction markets: Crowdcast, Inkling, HubDub, yahoo tech buzz, InTrade, Bet2Give, Hollywood Stock Exchenge
  • BRAIN – Behavioral Robust Aggregation of Information in Networks
  • Transcript

    • 1. Crowdsourcing and Markets in the Social Media Age Thomas Sandholm—Research Scientist, HP Labs, Palo Alto December 17, 2009 1 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 2. Information Abundance and Attention Scarcity – Information overflow on mobile devices •Small visual real-estate •Limited bandwidth •Limited input capabilities – How can crowdsourcing, markets, and context improve the mobile Web experience? 2 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 3. Agenda – Crowdsourcing – Markets – Social Media – Examples – SCL Projects – HP Gloe 3 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 4. CROWDSOURCING 4 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 5. Wisdom of Crowds – Surowiecki: The Wisdom of Crowds (2004) •Skepticism about dumb mobs •Crowds can be smarter than smartest individual if: 1.Diverse (otherwise no new ideas) 2.Independent (otherwise groupthink) 3.Decentralized (otherwise specialization is hard) 4.Aggregation (otherwise local knowledge is lost) 5 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 6. Crowdsourcing or Peer Production: Specialization and reputation drive long tail content production – Business model •Open call •Parallel problem solving •Vetting of solutions – Phenomenon •Historically: few publishers and millions of readers •Now: millions of publishers with few readers – Examples •Wikipedia, YouTube, Linux, Digg 6 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 7. Dynamics of Peer Production Why do people contribute to social media? – Lack of attention reason to stop contributing – Feedback loop of attention leads to power laws – Negligible part of content produced by majority of users – Negligible number of users produce majority of content – Hubs of well-connected users vital to dissemination – Persistence paradoxically inversely correlated to success 7 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 8. MARKETS 8 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 9. Market Properties Surowiecki’s fourth condition – Aggregation of decentralized local knowledge – Determine value of goods •Price varies until supply and demand are in equillibrium •Self-adjusting and decentralized – Walras’ Law in General Equilibrium Theory •Sum of excess demand across all markets equals zero – Market Mechanism: •Incentive compatible, individually rational, strategy proof •Incentive to participate truthfully, non-gameable •Selfish optimization leads to welfare •Effective high-quality, truthful information signals 9 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 10. Prediction or Information Markets Focus on information aggregation and prediction – Voting with costs and payoffs – 1988 Forsythe, Nelson, Neumann: Iowa Electronic Markets •Predict outcome of political races •Polling less accurate due to phrasing of question •Real money forces truthful behavior – 2003 Hanson: DoD PAM ―Terrorism Futures‖ •Public outcry – unethical to bet on terrorism attacks •Publicity – Crowdcast, Inkling, HubDub, Bet2Give •Same games, some real for-profit markets – Yahoo Tech Buzz, Google internal information flow markets •Cube neighbors influence betting behavior 10 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 11. SOCIAL MEDIA 11 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 12. Web 2.0 Social Media Apps Drove content production paradigm shift – Long tail content •Unpopular content gets published – Grass root reputation •meritocracy •open APIs for mashups – Collaborative filtering •Amazon book recommendations – The network effect •More users more quality opposite to Web 1.0 – Social networks are leveraged to disseminate information •Viral marketing •Friends determine what you see – Flickr, MySpace, YouTube, Facebook, Twitter •Not technology leaders but grabbed critical social mass •Innovators in how people interact 12 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 13. Context-aware applications Location, Social, Time, Weather Conditions – Mobile devices more personal •Already used to interact with friends – Sensors give more information to applications •No explicit user involvement – iPhone paved the way for the mobile Web •Full-featured Web browsers on smartphones – Affordable unlimited 3G data plans – Privacy opt-in •Intrusive apps more accepted if they have a social value 13 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 14. Location Based Services Pull or push content based on sensed location – Geography-aware service on mobile device – GIS for mobile phones – GPS + Internet on smartphones – Find what’s around you – Map based, AR based or Distance/Popularity Listings – Google Navigation/Maps, Wikitude.Me, Layar, Sherpa, Where, GeoVector, Loopt 14 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 15. EXAMPLES 15 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 16. Digg – a crowdsourced newspaper – Crowd-rendered front page – Novelty and popularity tradeoff – Update frequency unmatched 16 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 17. Delicious – social bookmarking – Share bookmarks with friends – Find popular bookmarks – Search by tags and tag clouds 17 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 18. Google AdWords – bidding for page prominence – Market mechanisms used to leverage attention economy – Key word auctions – Non-intrusive, relevant presentation – Virtually all of Google’s revenue 18 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 19. SOCIAL COMPUTING LAB PROJECTS 19 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 20. BRAIN – Prediction of events in small groups – Forecasting in teams biased towards ―loudest‖ member – When members put a bet on their forecast they predict more carefully and accurately – Risk attitudes of members matter, when normalized away the weighted prediction becomes more accurate 20 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 21. Tycoon – Market based computational resource allocation – Resources capacity allocated proportional to individual bids and inversely proportional to aggregate bids – q = b/(b+y) – Variable pricing, self adjusting to demand – Similar properties to second bid auction but converges quicker and has no discrete clearing times 21 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 22. HP Gloe 22 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 23. Idea Vote on web page to location mappings – Popularity search by radius, aggregation by URL – Social filtering – Folksonomy of hierarchical channels – Cyberspace notes – Votes governed by market economy 23 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 24. Popularity Ranking and Social Filtering 24 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 25. Folksonomy of hierarchical channels Restaurants Pizza Restaurants Pizza Restaurants Burgers Restaurants Diners 25 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 26. Cyberspace notes 26 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 27. Votes governed by market economy – Limited recommendation budget •American Idol type voting – Contributions controlled by currency •Earn, pay, penalties, income streams – Optimal budget allocation •Across regions in marketing campaigns •Across hierarchical key words – Voting minimal effort but truth-telling enforced •Restaurant services forcing you to leave comments to vote – Maximize information obtained from crowd •Value distribution beyond 5 star ratings 27 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 28. Demo – Launched on Android market Dec 1st – ~6 million recommendations, ~8000 channels, ~150 users – Data from Wikipedia, TripAdvisor, Panoramio, WikiTravel, POI Plaza, IMDb, DBPedia, Geonames, Google, Twitter, Bing 28 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 29. 29 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 30. 30 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 31. Research Problems – Design a market that gives incentive to users to contribute valuable mappings – Visualization, control and optimization techniques to trade off popularity (clicks and recs), novelty, and distance – Dynamic content provisioning, recommendation decay – Optimized channel and location-based bidding strategies – Data analytics, e.g. behavioral patterns in Web page recommendations 31 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 32. Summary – Crowdsourcing can be a very effective technique to offer long tail content if certain conditions are met – Markets can be used to control the quality of contributions and to aggregate local information concisely – Your social network provides a way to effectively filter and discover new information 32 © Copyright 2009 Hewlett-Packard Development Company, L.P.
    • 33. Q&A 33 © Copyright 2009 Hewlett-Packard Development Company, L.P.