2012 1030 presentation for sentiment conference


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I only had 7 minutes and it was right before lunch, hence the bread analogy. I focused on one of DataSift's truly unique features---the ability to do real time sentiment analysis on Social Content. Email me at rob.bailey@datasift.com if you'd like to learn more.

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  • Dell has a lar
  • Dell has a lar
  • Dell has a lar
  • Dell has a lar
  • 2012 1030 presentation for sentiment conference

    1. 1. Using SocialSentiment to Track RealTime Public Opinion Rob Bailey CEO, Datasift rob.bailey@datasift.com Twitter: @RMB
    2. 2. Most Powerful Platform For Real Time Social 1. Ingestion 2. Cleaning & 3. Enrichment & 4. Distribution Normalization FilteringWe ingest petabytes Using proprietary Each Social item Enriched, filtered of Social data from technology, we scrub gets tagged 40+ data is sent back out50+ global sources in the data to eliminate different ways (eg through enterprise Real Time with fully noise/spam & with Klout score) in grade API to 250+ redundant, push- normalize it <300 milliseconds customers based systems We do all of this in about half a second. 1
    3. 3. Sentiment in Social Is Like Bread 2
    4. 4. Sentiment in Social Is Like Bread Fresh is better. 3
    5. 5. Freshest Sentiment Analysis• We filter in real time, with latency < 300 MS• Set up new filters in minutes• Currently work with Lexalytics• We cover English, German, Portuguese, Spanish, French• 10 more languages coming 4
    6. 6. Benefits of Real Time Sentiment• Capture events in real time• Instantaneous drill-downs on drivers• Beat the competition (News, Finance)• Understand your audience faster 5
    7. 7. CASE STUDY: US Presidential Debates• Both candidate’s sentiment levels dropped when they attacked• Obama scored big with the bayonet comment• Delayed drop for Romney with Syrian & sea comment 6
    8. 8. CASE STUDY: Women Hate RIMWomen were better predictors than men about negativemarket reaction to the news. 7
    9. 9. CASE STUDY: Facebook IPOPublic sentiment on Twitter was a strong indicator of where the stock price would move next. 8
    10. 10. Sentiment in Social Is Like BreadNot everyone can handle it. 9
    11. 11. Hard To Replicate Technical Infrastructure DataSift Infrastructure HighlightsPickle is ourmassively paralleland scalable clusterof virtual machinesthat interprets, We deliver real-compiles and time data with veryevaluates low latency (subcustomer-created 200ms that ourfilters (expressed in platform adds.)CSDL) against data through ourevery single HTTP streamingincoming message engine called Meteory that is built on Node.JS We ingest data from over Our billing platform 50 Social manages licenses sources & & billing across 850+ news hundreds of sources in real customers and time & use 50+ content redundant sources in real systems to time, 5 min compensate increments for sometimes unreliable partner APIsWe use a variety of queing Our data store is based upon a bespoke deployment of Hadoop/HBasetechnologies including and our own low level Virtual Machine. Currently we have 1 PetabytesRabbitMQ to ensure of storage & are the only company worldwide to offer 2+ years ofconstant flow of data Augmentations covers all of the data services which either perform a 10 historical Social data real-time data analysis or lookup data from 3rd party data sets of pre-computed data.
    12. 12. Why Real Time So Important• Catch problems before they explode• Set up new searches quickly• Competitors are watching• Customers are increasingly impatient 11
    13. 13. Sentiment in Social Is Like Bread GET STARTED: hello@datasift.com GET INFORMED: @RMB 12