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Social data mining beyond keywords, Francesco D’Orazio @abc3d @ Big Data London, O’Reilly Strata Conference Special, October 1st 2012 and to Big Data World Congress London, November 7th 2012 …

Social data mining beyond keywords, Francesco D’Orazio @abc3d @ Big Data London, O’Reilly Strata Conference Special, October 1st 2012 and to Big Data World Congress London, November 7th 2012

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  • 1. Social Data !Beyond Keywords Francesco D’Orazio @abc3d www.facegroup.comBig Data Congress, London, November 7 2012
  • 2. We have beenasking thewrong question
  • 3. “We talk of the relationshipsconsumers have with our brands as ifthey were primary but the data pointsto things being otherwise.Consumers’ most valuablerelationships are not with brands butwith other consumers” Mark Earls
  • 4. Social data allow us to learn aboutthe relationships and interactionsbetween consumers and how brandscan fit into that equation  Cosmic 140 © Information Architects, Inc. 2010
  • 5. Social data allows us to see how interactions play out at individual level (microscope)
  • 6. Social data allow us to see howinteractions play out at network level(the macroscope)
  • 7. The codebehind atweet
  • 8. Currently we look at social media data ! like a butcher looks at a carcassCutting bykeywords Aggregating by channels Weighting by influence
  • 9. © Alexandre Farto aka Vhils 2010 Most Social Media Monitoring platforms focus on just Content
  • 10. © Alexandre Farto aka Vhils 2010 But we also wanted to understand Context and Behaviour
  • 11. © Thomas Doyle 2010 So we designed new research frameworks and social data mining tools
  • 12. Social Media vs Social Data Social media is the set of applications and platforms allowing Social data is the people to participate in collective information online social activities produced by millions of people as they actively participate in online social activities. 13
  • 13. Social Media vs Social Data 14
  • 14. Social Media vs Social Data 15
  • 15. Dimensions of Social Data Content Demographics Behaviours Social Graph Interest Graph 16
  • 16. What makes social data ‘big’?Large volumesReal-time collectionReal-time analysisInteractivityFull-Text Weavrs Emotion Map
  • 17. 1!TOPIC/BRAND tracking By keywords Share of Voice
  • 18. 2!AUDIENCE mapping > brand graph By keywords By audience Share of Voice Share of Mind
  • 19. 3!CLUSTER tracking > real-timesegmentationDynamicSegments Real-time Audience Insights
  • 20. 4! CONTENT diffusion > where, how and who is sharing the content
  • 21. 5!INFLUENCE mapping > hubs &connectors by volumes, visibilityand engagementInfluence by Volume Influence by Visibility Influence by Engagement
  • 22. 6!SOCIAL CRM > efficientworkflow with automaticlabeling and predictive modeling
  • 23. 7!Augmentation > layering socialdata on a Panel or a Community
  • 24. 8! SOCIAL SIMULATIONS20 participants 20 alpha-bots designed by them 20 beta-bots tested and fine- tuned by us 20 beta-bots cloned 20 times each (400 beta-clones active over a 2 weeks period)
  • 25. 9!REALITY MINING
  • 26. Social science +Computational Social data Social Science + Computation  
  • 27. CONTINUOUSITERATION: play with awider range ofhypothesis to solve aproblem.Pulsar Social Data Mining platform 31
  • 28. CONTINUOUS ITERATION: starting with 0 hypothesis> finding out what I don’t know I don’t knowIs Big Data producing a new epistemology? 32
  • 29. Thank you francesco d’orazio, @abc3d! www.facegroup.com