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When to use the different text analytics tools - Meaning Cloud

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Classification, topic extraction, clustering... When to use the different Text Analytics tools?
How to leverage Text Analytics technology for your business
MeaningCloud webinar, February 8th, 2017
More information and recording of the webinar https://www.meaningcloud.com/blog/recorded-webinar-use-different-text-analytics-tools
www.meaningcloud.com

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When to use the different text analytics tools - Meaning Cloud

  1. 1. Text Analytics Tools: When and How to Use Them February 8th, 2017 Webinar
  2. 2. Text Analytics Tools Before we get started… Presenter How to participate • Send questions with the chat feature, or • Click the “Raise your hand” button to speak and we’ll enable your mic • Afterwards, you’ll be able to access a recording of the webinar and its contents as tutorials on our blog Antonio Matarranz CMO
  3. 3. Text Analytics Tools The purpose of this webinar… Learn what the main Text Analytics functions are and what they can do for us
  4. 4. Text Analytics Tools Agenda  Introduction to text analytics  Application scenarios. Benefits and challenges  Text analytics functions. Description and use cases  Quality of text analytics tools  A look at MeaningCloud’s roadmap  Conclusions and Q&A
  5. 5. Text Analytics Tools Why should we be using text analytics? Structured data Unstructured content
  6. 6. Text Analytics Tools Opinions Facts Concepts Organizations People Semantic Analysis Relationships Themes Text analytics Extract meaning and actionable insights from unstructured content Automation of costly manual activities
  7. 7. Text Analytics Tools Text analytics functions  Information extraction, NER  Categorization  Clustering  Sentiment analysis  Morphosyntactic analysis  …
  8. 8. Text Analytics Tools APPLICATION SCENARIOS
  9. 9. Text Analytics Tools Social media analysis Management of user generated content Security & defense Challenge: informal language Understand the conversation in social networks, blogs, forums… Brand and reputation monitoring Signals, customer journey, intent, social leads User profiling
  10. 10. Text Analytics Tools Voice of the Customer (VoC) / Customer Experience Extend your view of the customer to new, non traditional data sources: comments in surveys, contact center interactions, social conversations… Demographic data CRM / Mktng. automation Contact Center interactions Devices Product use Navigation Social 360º vision Orders and Payments Unsolicited, unstructured sources contribute to create integrated 360º customer view Integrated customer view helps provide personalized, consistent, context-specific and relevant experiences
  11. 11. Text Analytics Tools Voice of the Citizen/Voter Analysis of social opinions and segmentation allow to understand citizen attitudes and behaviors Citizen profiling. Opinions and trends about political situation, government and their services Emergency detection and lifecycle management
  12. 12. Text Analytics Tools Voice of the Employee / People Analytics Leaders Regular Army Geeks Improve workforce understanding Analysis of surveys, performance reviews, exit interviews, CVs, communications Attitudes/skills/behaviors most present among top performers Effective talent management and employee retention
  13. 13. Text Analytics Tools Semantic analysis of content for enhanced exploitation and relation Better understanding and use of archive. Generation of high-value content Improved audience engagement thanks to personalization, recommendation and topical contents New ways of monetization: targeted advertising, distribution and syndication Moderation and understanding of user generated content Intelligent content (media, publishers)
  14. 14. Text Analytics Tools For knowledge-intensive industries and departments Leverage the tacit knowledge hidden in your document repositories Semantic tagging and analysis of documents for advanced retrieval and exploitation Knowledge management
  15. 15. Text Analytics Tools E-discovery and regulatory compliance Analysis of electronic documents and communications to discover evidence Legal proceedings, regulated industries (e.g., financial services) Sources: documents, phone call transcriptions, email, chat, social… Low latency enables criminal behavior prevention and quick response
  16. 16. Text Analytics Tools TEXT ANALYTICS FUNCTIONS
  17. 17. Text Analytics Tools MeaningCloud: “Meaning as a Service” (SaaS and on-premises) Sign up, and use it for FREE at http://www.meaningcloud.com
  18. 18. Text Analytics Tools MeaningCloud’s APIs Identifies occurrences of names of people, organizations, abstract concepts, quantities, etc. Theme classification according to predefined taxonomies Identifies general and attribute-level polarity Distinguishes among 60 languages Detailed morphosyntactic analysis Evaluates the impact of opinions on several reputational axes Discover meaningful topics and similarities among texts without relying on predefined taxonomies
  19. 19. Text Analytics Tools Add-in for Excel  An experience fully integrated into Excel  Easy to use - No programming!  The most convenient way to evaluate, prototype, and use MeaningCloud 19
  20. 20. Text Analytics Tools Topic Extraction API Disambiguate appearances of brands, companies, organizations, people, concepts… and many more  Contextual disambiguation • Apple = company (not fruit)  Coreference  Based on standard ontology  Extendable/customizable dictionaries In a filing with the SEC today, Apple revealed that CEO Tim Cook has donated the equivalent to approximately $6.5 million in Apple stock shares to charity this week. Since becoming CEO in 2011, Cook has promoted charity as a key part of Apple’s mission. Upon taking over, Cook initiated an employee charity program. Apple has also expanded its offerings for employees to help their communities. Topic detected Semantic information Tim Cook Person, Timothy Donald Cook, Executive Apple Inc. Apple Company, Apple Inc., Technology, USA SEC Organization, Securities and Exchange Comission, Government, USA $6.5 million Monetary amount, USD, 6.5 million charity Concept, charity
  21. 21. Text Analytics Tools MeaningCloud: standard ontology Built-in ontology  437 nodes  78 themes  250,000+ lemmas/language  Continuously updated https://www.meaningcloud.com/developer/ documentation/ontology
  22. 22. Text Analytics Tools What is topic extraction for?  Sophisticated detection of appearances/mentions of brands, people, companies, concepts… • Context-aware disambiguation • Considering variants • Coreference  Application examples: • Key word extraction • Document annotation: news, books, emails, records • Social media monitoring • Voice of the Customer / Employee / Citizen / Patient analysis • User profiling (interests)
  23. 23. Text Analytics Tools Text Classification API (featuring standard models, e.g. IAB) Mix machine learning and rules to accurately classify text according to predefined categories The World Cup is the best way to see the potential football can have for your inbound travel, economic success and positive public image: The 2006 World Cup in Germany was a prime example of this power with: $200+ per day average tourist spending, 50,000 new jobs created, 18 million people at Fan-Fests, total worldwide TV viewership at 30 billion and 4.2 billion official webpage views. In a survey, 90% of foreigners who visited the World Cup said they felt welcome there and would recommend Germany as a holiday destination. "The World Cup marks an enormous gain in Germany's image, even if it's difficult to put an economic figure on this change in image, the economy as a whole will certainly benefit from it." the German economics minister, Michael Glos, said. Categories Relevance Sports – World soccer 0.7 Travel - Europe 0.2 Arts & Entertainment - Television 0.3 IAB (English)  Hybrid technology • Machine learning and/or rules  Features standard classification models • IPTC (news), IAB (advertising), EuroVoc (public administration), Social Media, Business Reputation  Customizable classification models
  24. 24. Text Analytics Tools MeaningCloud: standard classification models ‘Out-of-the-box’ support of well-known predefined classification standards  IPTC: news  IAB: targeted advertising  EuroVoc: public administration  Social Media: social conversations … and more to come https://www.meaningcloud.com/developer/documentation/supported-models
  25. 25. Text Analytics Tools Classification technologies  Classifiers use patterns/vectors that represent each category  Technologies to generate those representations • Statistic • Rule-based Training documents for category Machine learning Rules for category Rule codifier Rule 1 Rule 2 Rule 3 Rule 4 Category representation Category representation
  26. 26. Text Analytics Tools What is text classification for?  Theme categorization: category is inferred from whole content • Text is similar to others belonging to the category • Text verifies certain rules • In general it is not necessary that certain term explicitly appears  Application examples: • Document annotation: news, books, emails, records • Voice of the Customer / Employee / Citizen / Patient analysis • Conversation analysis in social media • User profiling (interests)
  27. 27. Text Analytics Tools Text Clustering API Group similar texts and discover meaningful themes 27 Financial crisis Greenhouse effect  No predefined taxonomy required (unsupervised learning)  Text-specific processing  Text grouping based on • Adherence to a theme • Content similarity Cluster title Size Score Document list Financial crisis 4 0.96 Doc1, Doc4, Doc7, Doc8 Greenhouse effect 5 0.34 Doc2, Doc3, Doc5, Doc6, Doc9
  28. 28. Text Analytics Tools What is text clustering for?  Grouping of similar texts and discovery of meaningful themes • Without relying on predefined taxonomies  Application examples: • Duplicate detection • Discovery of structure in document collections • Discovery of conversation themes in social media • Discovery of the "new voice" of Customer / Employee / Citizen / Patient
  29. 29. Text Analytics Tools Sentiment Analysis API Assign multilevel polarity to entities and other aspects, discriminate facts from opinions and detect irony Aspect Sentiment Excelsior Hotel - landscapes P+ Excelsior Hotel - rooms N- General NEU, DISAGREEMENT, SUBJECTIVE, NON IRONIC  5-level polarity (plus absence of polarity) scoring  Aspect-based analysis  Objective (fact) / subjective (opinion) discrimination  Irony detection (beta)  Customizable sentiment models Excelsior Hotel has the most amazing landscapes I've ever seen, but the rooms are disgusting.
  30. 30. Text Analytics Tools What is sentiment analysis for?  Opinion analysis and mining (polarity) • General and at attribute/aspect level • Fact/opinion discrimination  Application examples: • Social media monitoring • Voice of the Customer / Employee / Citizen / Patient analysis
  31. 31. Text Analytics Tools Lemmatization, PoS and Parsing API Detailed morphosyntactic and semantic analysis  Syntactic analysis  Lemmatization  Part of Speech tagging  Relationships  Quotations  Topics: entities, concepts, etc.  Sentiment analysis
  32. 32. Text Analytics Tools What is morphosyntactic analysis for?  Analysis of a text‘s deep structure • Morphological, grammatical, semantic  Application examples: • Text proofreading: spell, grammar and style • Support for the detection of semantic relationships, e.g., “CompanyX has invested in CompanyY” • In MeaningCloud’s case, applications of Topics Extraction and Sentiment Analysis Use it for FREE at www.mystilus.com
  33. 33. Text Analytics Tools User Profiling API Use the profile and content generated by the user to infer his demographic & psychographic attributes 20% of companies say process digitization yields actionable #analytics Is your IT team talking SMAC (#social, #mobile, #analytics, & #cloud)? Five Rules of Modern Icon Design http://bit.ly/1y3B6i6 What Twitter Can Be. http://wp.me/p2Gq8C-6E Just if they'd play nice with the ecosystem ... #socialtv #recommendation What your name says about your age, where you live, your politics & your job http://wapo.st/1RkqDcA Londoner, hooked on data science, NLP and REST. Social posts Social profile Atribute Value Person/Organization Person Gender Male Age 25-35 Location London Occupation Engineer Brands IBM  Demographic  Person /organization  Gender  Age  Location  Occupation  Psychographic  Affinities  Lifestyle…
  34. 34. Text Analytics Tools What is user profiling for?  Demographic and psychographic profiling of users  Application examples: • Audience/Market understanding and segmentation • Community analysis in social media • Influencer marketing
  35. 35. Text Analytics Tools IS THIS ALL A QUESTION OF PRECISION?
  36. 36. Text Analytics Tools Just how precise is precise? Precision is relative  Even experts aren’t 100% precise • Tests involving human analysts: 85-95% agreement  Along with precision, recall is also important High precision High recall High precision Low recall Low precision High recall Identified by algorithm
  37. 37. Text Analytics Tools Accuracy: precision & recall  Precision and recall are inversely related • Trade-off needed  Requirements are application-specific • Brand monitoring in social media: high precision, low recall • Counter-terrorism : high recall, low precision
  38. 38. Text Analytics Tools Opinions The sentence “The highest interest rate in industry!” is…  Positive, if talking about savings  Negative, if talking about mortgages Customized linguistic resources improve accuracy Mentions  Names of banks and financial companies, e.g., JPMorgan, BNP Paribas, Citibank  Product names, e.g., Your Way Account. Compass Account… Themes Example: analysis of a bank’s customer opinions Products Accounts Checking Savings Borrowing Credit Mortgage Channel Office Phone Internet
  39. 39. Text Analytics Tools MeaningCloud customization tools
  40. 40. Text Analytics Tools Customization tools  Create your own dictionaries, classification models, and sentiment analysis  Graphical user interface - no programming!  Improve precision & recall Learn more about customization in this webinar
  41. 41. Text Analytics Tools A vew into the future MeaningCloud’s roadmap  Extension for RapidMiner: combine data and text analytics  New languages: Russian, Chinese, Arabic… and many more  New APIs: Summarization, Parts of Document  Vertical Packs: VoC (general and several industries), VoE, Health  Insight Extractor: a granular categorizer and information extractor based on semantic rules Q1 2027 Q2 2017 Q3 2017 Q4 2017 Q1 2018 Extension for RapidMiner Insight Extractor Aditional languages Summarization API, Parts of Document API Vertical Packs
  42. 42. Text Analytics Tools In conclusion Tools that turn text into insights Countless applications Accuracy = customization MeaningCloud: specialists in text analytics
  43. 43. Text Analytics Tools Q & A
  44. 44. Text Analytics Tools Stay tuned to our emails and blog We’ll be posting a recording of the webinar and its contents as tutorials soon
  45. 45. Text Analytics Tools Thank you for your attention! Questions, suggestions... Antonio Matarranz CMO amatarranz@meaningcloud.com http://www.meaningcloud.com

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