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Synergies Between Search and Social Metrics
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Synergies Between Search and Social Metrics

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My talk from: New Metrics for New Media:

My talk from: New Metrics for New Media:
Analytics for Social Media and Virtual Worlds

http://mediax.stanford.edu/WSI/metrics.html

@Media X Stanford 2009

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  • Me: Y! Research after Northwestern, PhD CS, Adjunct at Medill, CMEX @ Ames, Studio Art instructor for 5 years during my BS/MS in AI
  • How do people become aware of services and applications, and integrate them into their lives? What are tipping points for awareness and for increased usage?How/when/when do people share knowledge (digital content)?(3) How is the increase in information appliances like smart phones and always-on internet displays in the home and in public spaces changing knowledge sharing and internet service use?
  • This goes beyond A+B testing & hill climbing.
  • Are they really watching or talking to each other?
  • Reciprocity means nothing for core search as we know it

Synergies Between Search and Social Metrics Synergies Between Search and Social Metrics Presentation Transcript

  • Synergies BetweenSearch and Social Metrics
    @ mediaX • Stanford University
    David A. Shamma • Yahoo! Research
  • Internet Experiences Group (IEG)
    Yahoo! Research
  • Internet ExperiencesYahoo! Research
    Elizabeth Churchill
    M Cameron Jones
    Ayman
  • IEG Research Areas
  • IEG Research Areas
  • Methods
    Experience measurement through method triangulation:
    • Literature/business analysis
    • Site reviews
    • Data visualization
    • Surveys
    • Field studies
    • Prototypes
    • Activity log analysis
    Psychology, Sociology, Anthropology,
    Linguistics, Computer Science, Design
  • Why are these people here?
    Dolores Park, San Francisco July 2006.
  • People Like Video
    FIFA World Cup Final 2006.
  • Legacy Web Video
  • Legacy Metrics
    • Page Views
    • Playback
    • Tags
    • Links/Embed
    • Favorites
    • Comments
    • People
    • Shares
  • Yahoo! Zync
  • What to Collect to measure engagement?
    Type of event (Zync player command or a normal chat message)
    Anonymous hash (uniquely identifies the sender and the receiver, without exposing personal account data)
    URL to the shared video
    Timestamp for the event
    The player time(with respect to the specific video) at the point the event occurred
    The number of characters and the number words typed (for chat messages)
    Emoticons used in the chat message
  • A Short Movie
  • Percent of actions over time.
  • Volume of actions over time.
  • Chat follows the video!
    CHAT
  • Social Networks
  • Boundary Objects
  • Core Stats (opt-in)
    April 1, 2009 through April 7, 2009 (inclusive).
    3.25 million events (URLs, chat, volumes, pause events).
    24,258 users • 24,506 sessions
    Of these users, 35.29% (μ=2:02, σ= 2:72,σ2= 7:40) of the users engaged in more than one session during that week
    76,762 URLs, 23% shared in more than one session.
    Over 99% of the shared videos came from YouTube.
    Approximately 2% of all the URLs sent within Yahoo! Messenger at-large.
  • Reciprocity
    43.6% of the sessions the invitee played at least one video back to the session’s initiator.
    77.7% sharing reciprocation
    Pairs of people often exchanged more than one set of videos in a session.
    In the categories of Nonprofit, Technology and Shows, the invitees shared more videos to the initiator (5:4, 9:7, and 5:2 respectably).
  • What are they doing?
    Dolores Park, San Francisco July 2006.
  • Now they would be Tweeting!
    Dolores Park, San Francisco July 2006.
  • People Tweet While They Watch
  • CurrentTV: Hack the Debate
  • Tweet Crawl
    Three hashtags: #current #debate08 #tweetdebate
    97 mins debate + 53 mins following = 2.5 hours total.
    3,238 tweets from 1,160 people.
    1,824 tweets from 647 people during the debate.
    1,414 tweets from 738 people post debate.
    577 @ mentions (reciprocity!)
    266 mentions during the debate
    311 afterwards.
    Low RT: 24 retweets in total
    6 during
    18 afterwards.
  • 1st Presidential Debate Sampled Tweet Volume over time.
  • 1st Presidential Debate Sampled Tweet Volume over time.
    CHAT
  • Video Segmentation
  • #tags as boundary objects
  • Hey @newshour!
  • High Centrality
  • Topics follow but not aligned
  • In Search of Social…
    Instrument for Engagement
    Privacy
    Volume of Interaction
    Search for Expression
    Crawling samples
    Re-query for missed data
    Identify pragmatics of the medium
    Twitter can be content free
    Twitter isn't necessarily social
    Find meaningful reciprocity
    Merge Classical Methods with Social Metrics
    Model social interaction as it is represented and beyond
  • thanks to echu, lyndon, mcjones!
    Fin.
    aymans@acm.org • http://shamurai.com