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Taxonomy and Social Media Social Taxonomies

Discover how taxonomy and text analytics can be applied to social media to gain real value and unlock new opportunities in this changing world.

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Taxonomy and Social Media Social Taxonomies

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  1. Taxonomy and Social MediaSocial Taxonomies Tom ReamyChief Knowledge Architect KAPS Group Program Chair – Text Analytics World Knowledge Architecture Professional Services http://www.kapsgroup.com

  2. Agenda • Introduction • It’s a Different World • Content and Intent • New Approaches • To Taxonomy • Text Analytics • New Applications – and Opportunities • Conclusion

  3. Introduction: KAPS Group • Knowledge Architecture Professional Services – Network of Consultants • Applied Theory – Faceted & emotion taxonomies, natural categories Services: • Strategy – IM & KM - Text Analytics, Social Media, Integration • Taxonomy/Text Analytics, Social Media development, consulting • Text Analytics Quick Start – Audit, Evaluation, Pilot • Partners – Smart Logic, Expert Systems, SAS, SAP, IBM, FAST, Concept Searching, Attensity, Clarabridge, Lexalytics • Clients: Genentech, Novartis, Northwestern Mutual Life, Financial Times, Hyatt, Home Depot, Harvard Business Library, British Parliament, Battelle, Amdocs, FDA, GAO, World Bank, Dept. of Transportation, etc. • Program Chair – Text Analytics World – March 29-April 1 - SF • Presentations, Articles, White Papers – www.kapsgroup.com • Current – Book – Text Analytics: How to Conquer Information Overload, Get Real Value from Social Media, and Add Smart Text to Big Data

  4. New Content CharacteristicsIt’s a Very Different World • Scale – orders of magnitude – 100’s of millions, Billions • Speed – 20-100 million a day • Size – Twitter, Blogs, forums, email • 140 characters to a few sentences • Quality – misspellings, lack of structure, incoherence • Conversations – not stand alone docs • Can’t tell what a “document” is about without reference to previous threads • Purpose – communicate - social grooming, rant • Not exchange of ideas, policies, etc. • Simple Content Complexity – single thoughts, simplicity of emotion

  5. New Content CharacteristicsIt’s a Very Different World – Search and Taxonomy • i tried very slow, NO GOOGLE search, some apps not working.. This is not a "with GOOGLE" My friend has incredible, that is much batter.. Anyways i returned samsung, replace incredible. What's great about it:  4" LCD What's not so great:  NOT A GOOGLE PHONE • (nt 2.0)willie John ci to/for: wanted to know about charges for pic mail for ;bill date 4/5/2010 | repeat: no | auth: pin | ptns affected: 7777777777 | information/instructions given: sup gave pic mail for free and gave adj for $ 2.40 new bal is $ 147.53 | any mobile, anytime: n | ir: yes | ir-email: n |

  6. New Content CharacteristicsIt’s a Very Different World – Topical Current Content • Content not archived (for users) • No real need for search (or just very simple search) • Very Poor (if any) metadata – not faceted search • Focus on phrases, sentences – not documents • Little need of a subject taxonomy • About emotions, things, products, people • Who are the users? They don’t need our help • Taxonomies, we don’t need no stinking taxonomies!

  7. It’s a Very Different World • So why are we talking about it at a taxonomy boot camp? • Taxonomy = structure (purists can leave now) • All of this content is a rich source of research material • Companies are mining this resource and they need to add structure to get deeper understanding • Varieties of structure: • Simple topical taxonomies 2-3 levels • Emotion taxonomies, Ontologies and Semantic Networks • Dynamic taxonomies – built on public taxonomies, enterprise taxonomy – exposed in hierarchical triples . • Need more automatic / semi-automatic solutions • Advanced text analytics

  8. New Kinds of Social Taxonomies • New Taxonomies – Appraisal • Appraisal Groups – Adjective and modifiers – “not very good” • Four types – Attitude, Orientation, Graduation, Polarity • Supports more subtle distinctions than positive or negative • Emotion taxonomies • Joy, Sadness, Fear, Anger, Surprise, Disgust • New Complex – pride, shame, embarrassment, love, awe • New situational/transient – confusion, concentration, skepticism • Beyond Keywords – Need Text Analytics • Analysis of phrases, multiple contexts – conditionals, oblique • Analysis of conversations – dynamic of exchange, private language • Enterprise taxonomy rolled into a categorization taxonomy

  9. Case Study – Categorization & Sentiment

  10. Case Study – Categorization & Sentiment

  11. Taxonomy and Social Media: ApplicationsNew Range of Applications • Real Sentiment Analysis - Limited value of Positive and Negative • Degrees of intensity, complexity of emotions and documents • Contextual rules – “I would have loved X except for the battery” • Expertise Analysis • Experts think & write differently – process, chunks • Categorization rules for documents, authors, communities • Behavior Prediction–TA and Predictive Analytics, Social Analytics • Crowd Sourcing – technical support to Wiki’s • Political – conservative and liberal minds/texts • Disgust, shame, cooperation, openness

  12. Taxonomy and Social Media: ApplicationsPronoun Analysis: Fraud Detection; Enron Emails • Patterns of “Function” words reveal wide range of insights • Function words = pronouns, articles, prepositions, conjunctions, etc. • Used at a high rate, short and hard to detect, very social, processed in the brain differently than content words • Areas: sex, age, power-status, personality – individuals and groups • Lying / Fraud detection: Documents with lies have • Fewer and shorter words, fewer conjunctions, more positive emotion words • More use of “if, any, those, he, she, they, you”, less “I” • More social and causal words, more discrepancy words • Current research – 76% accuracy in some contexts • Text Analytics can improve accuracy and utilize new sources

  13. Taxonomy and Social Media: ApplicationsBehavior Prediction – Telecom Customer Service • Basic Rule • (START_20, (AND, • (DIST_7,"[cancel]", "[cancel-what-cust]"), • (NOT,(DIST_10, "[cancel]", (OR, "[one-line]", "[restore]", “[if]”))))) • Examples: • customer called to say he will cancell his account if the does not stop receiving a call from the ad agency. • cci and is upset that he has the asl charge and wants it offor her is going to cancel his act • ask about the contract expiration date as she wanted to cxltehacct • Combine sophisticated rules with sentiment statistical training and Predictive Analytics and behavior monitoring

  14. Taxonomy, Text Analytics, and Social MediaConclusions • Social Media is a Different World • Content, Scale, Questions • New Types of Taxonomy • Smaller, more dynamic subject taxonomies • Appraisal, Emotion, Things, Motivations, Actions, etc. • Taxonomists – Time to Explore new structures • Ontologies, semantic networks, all of above • Text Analytics – needs good taxonomy design – levels, etc. • Adds a platform – flexible and powerful auto-tagging, • Result: New Types of Applications • Stand alone and with standard search/taxonomy • Merge data and text, external and internal

  15. Questions? Tom Reamytomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

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