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Metavana Technology Overview
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Metavana Technology Overview

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A basic introduction to Metavana's text-based sentiment analysis technology

A basic introduction to Metavana's text-based sentiment analysis technology

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Metavana Technology Overview Presentation Transcript

  • 1. Technology Overview
  • 2. Conceptual Overview Focused Web 1. Crawling Classification Engine Twitter API / User Interface 2. 3. Social Facebook Sentiment NPS Score Polarity A. Collect & B. Analyze & C. Expose & Preprocess Classify Interpret
  • 3. A. Collect & Preprocess Business Domain Source “Seeds” Focused Web Crawler Content & URL Filtering Fail? Ignore Hyperlinks Extracted & Archived Multithreaded Downloader of Web Pages Information & Metadata Domain Extraction Database
  • 4. B. Analyze •& Classify Classification Engine • • Filter & Clean Stop Words Extract Keywords Calculate Frequency & Number • Phase Transform for Relevancy • Define Category Spectrum • Identify Sentiment Words Sentiment • Identify Polarity of Sentiment Engine • Predictive Polarity • Filter Sentiment Sentences • Calculate Corpus NPS Score Social NPS • Assign NPS Scores to each Sentence Calculation • Compare with NPS for a given Domain
  • 5. NPS Survey Results vis-à-visWeb-derived Social NPS ResultsDomain Satmetrix NPS Metavana sNPS Error MarginVerizon – ISP +12% +10% +/- 4%Verizon – Cellular +12.5% +12% +/- 4%Verizon – Cable +27.8% +29% +/- 4%AT&T – ISP +5% +5% +/- 4%T-Mobile – Cellular +11.5% +10% +/- 4%Eircom -24.1% -24% +/- 4%Virgin Media -17% -17% +/- 4%
  • 6. C. Expose & Interpret Web • Metavana.com UX • SparkScore™ • iPad / iPhone Domain Mobile • Android Database UX • Windows Phone • Data Feed • Custom Apps API • Appliance • Social CRM
  • 7. Completed “Domains” Airlines Automotive Antivirus Software Computer Laptops Computer Printers Cosmetics Hospitality (Hotels & Motels) Coffee & Tea
  • 8. Domains Under Development Credit Card Issuers National Commercial Banks Fashion & Luxury Distilled Spirits Cable TV Providers Telco Service Providers