Products & Solutions / Sentiment Analysis

SAS® Sentiment Analysis

Automatically pinpoint sentiment from the Web and electronic documents

SAS Sentiment Analysis collects (i.e., crawls) digital content sources, including mainstream Web sites and social media outlets, as well as internal organizational text sources. It then uses powerful statistical techniques and linguistics rules to extract the sentiment expressed in these text collections – providing summaries, identifying trends and creating graphical reports that describe the expressed feelings of consumers, customers and competitors in real time.

Output from SAS Sentiment Analysis can be stored in a document repository, surfaced in corporate portals and used as input to additional SAS Text Analytics software or even a search engine. It provides exceptional real-time processing speeds for large volumes of text.

Benefits

  • Evaluate sentiment and monitor changes over time.
  • Identify feedback sources to define new targets.
  • Continuously improve customer experience and competitive position.
  • Promote ongoing discovery with a closed-loop, integrated analysis environment.

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Features

  • Statistics and linguistics combined to provide more accurate sentiment analysis results
  • Context of features examined for accurate interpretations
  • Dynamic sentiment analysis
  • Easy-to-use interface for model development
  • Interactive workbench for model refinement
  • Updates on Web postings, reviews and opinions
  • Multiple languages natively supported

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Choose your own output schema with markup matcher.


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How SAS® Is Different

  • SAS Sentiment Analysis uses a hybrid approach based on statistical modeling and rule-based natural language processing (NLP) to automatically extract sentiments in real time or over a period of time from the Web or internal electronic document collections.
  • Ongoing model refinement enables you to focus on current opinions, identify changes as they occur and flexibly augment evaluations with new information – constantly improving the effectiveness of your analysis and providing quantified insights on products, services and brands not previously available from the manual review of Web and other electronic-based content.
  • Incorporating an extensive number of native languages and dialects, the software provides a detailed breakdown of text evaluations. Extrapolate information and create color-coded graphs to understand exactly what these commentaries mean in terms of overall expressed sentiment for your brand, products and services.
  • As part of an integrated framework, SAS Sentiment Analysis can be combined with categorization, extraction and text mining models so you can discover and extend existing taxonomy definitions to include the associated expressed sentiments. And as part of the SAS Business Analytics Framework, you can explore results in familiar reporting environments using SAS Business Intelligence and data visualization and discovery products.

Benefits

  • Evaluate sentiment and monitor changes over time. The software automatically extracts sentiments in real time or over a period of time with a unique combination of statistical modeling and rule-based natural language processing techniques. Built-in reports show patterns and detailed reactions.
  • Identify feedback sources to define new targets. By actively monitoring internal collections (such as call centers and the Web) combined with social networking sites (like Twitter and Facebook), the software shows where you're being discussed and what is being said. It automatically extracts feedback as content is crawled, filtering out the most important concepts so you can pursue promising opportunities.
  • Continuously improve customer experience and competitive position. The software searches for and evaluates internal and external content about your organization and competitors, identifying positive, negative, neutral and "no sentiment" texts – quantifying perceptions in the market.
  • Promote ongoing discovery with a closed-loop, integrated analysis environment. With ongoing evaluations, you can refine models and adjust classifications to reflect emerging topics and new terms relevant to your customers, organization or industry.

Features

Statistics and linguistics combined to provide more accurate sentiment analysis results
  • Provides a choice of approaches to sentiment analysis:
    • Statistical modeling: Provides predefined default parameters – that can also be configured – to identify the document sentiment from text.
    • Linguistic rules: Lets subject-matter experts define the elements to be examined for sentiment assessment.
    • Hybrid approach: Provides the unique ability to use both statistical rigor and linguistic rules to define sentiment models driving more detailed sentiment evaluations.
  • Ability to import and/or create concepts for evaluations.
Context of features examined for accurate interpretations
  • Supports complex linguistic rules for one or several matches of a term, regular expressions, part-of-speech tags and more.
  • Includes prebuilt tasks to simplify linguistic pattern identification. It offers:
    • Predicate rules to define semantic relationships between concepts.
    • Operators to locate related information with greater precision, such as co-referencing.
    • Identification of intermediate concepts that contain rules referenced by other concepts (shortens the rule-writing process).
    • Case-insensitive matching, so you can match both uppercase and lowercase terms.
Dynamic sentiment analysis
  • Permits improvements and/or changes over time with multiple model generation within the same project, and the ability to edit and test model modifications.
  • Allows subject matter experts to refine model performance with an easy-to-use point-and-click workbench.
  • Monitoring of results over time will inform model analysis refinement, identify emerging issues and establish comparisons to benchmark training sets to allow for continuous improvement.
Easy-to-use interface for model development
  • A mechanism to directly upload sentiment analysis models to the server reduces manual model deployment.
  • Keyboard shortcuts are available for interactivity, as well as enhanced search functionality assisting with model development activity.
  • Project wizard allows you to configure your project while it is being defined.
  • Panes in the interface simplify tasks and display more information, such as rule evaluations and search results.
Interactive workbench for model refinement
  • Graphics depicting sentiment are displayed to readily identify the resulting classification as positive, negative, neutral or unclassified.
  • Point-and-click exploration of classified text, drilling to detail as desired.
  • Enhanced report formatting improves results display.
  • Ability to add new concepts/entities to capture desired topics.
  • Word cloud report, based on predefined concepts, automatically illustrates extracted noun phrases.
  • Some workbench functionality is available through Web services APIs so documents can be programmatically added to different projects, exported, managed, searched, etc.
Updates on Web postings, reviews and opinions
  • High-performance, multithreaded crawler that can be deployed in a distributed and/or grid mode to maximize processing and support extremely large-scale crawls for both internal file system and Internet crawls.
  • Powerful linguistic technology is built in to extract URLs from Java scripts.
  • Crawler plugins are available for popular social media sites, including Google, Facebook, Twitter, Bing, BoardReader, Flickr, LinkedIn and Yahoo! scripts.
  • Web crawls can be interrupted and resumed or incrementally updated. The transversal depth of crawls can also be eliminated.
  • Markup matcher provides a point-and-click interface to simplify the extraction of fielded data from HTML or XML, specific to a site, and a stream or batch process to update new documents. Edit and test matches for both XPath and regular expression rules.
Multiple languages natively supported
  • Full suite of 30 native languages (plus dialects) available.
  • Supports Arabic, Chinese (both Simplified and Traditional), Czech, Danish, Dutch, English (US/UK), Farsi, Finnish, French (French/Canadian), German (New/Old), Greek, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Korean, Norwegian (Nynorsk/Bokmål), Polish, Portuguese (Portugal/Brazil), Romanian, Russian, Slovak, Spanish (Spain/South America), Swedish, Thai, Turkish, Ukrainian and Vietnamese.

Screenshots

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Multilevel taxonomies classify sentiment detail to pinpoint issues.

Multilevel taxonomies classify sentiment detail to pinpoint issues at a deeper level, including document, concept, attributes and subattributes.

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Graphics and user-friendly reports readily describe sentiment insights.

Graphics and user-friendly reports readily describe sentiment insights for exploring scored text and providing feedback to further refine models.

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Visually compare different types of models, from statistical, rule-based or hybrid algorithms.

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Use the point-and-click SAS Sentiment Analysis workbench to refine model classifications.

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Search for particular keywords within defined date ranges, and even categories by classified sentiment.

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Visually explore scored sentiment documents in charts – or, based on predefined categories, in phrase cloud format.

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Choose your own output schema with markup matcher.

With markup matcher for the SAS web crawler, you can choose your own output schema and normalize as you select the desired fielded content.

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System Requirements

SAS Sentiment Analysis is a standalone product that requires no other SAS modules.

Client Environment
  • Microsoft Windows (x86-32 and x64): Windows XP Professional, Windows 7**, Windows Server 2003 family, Windows Vista*, Microsoft Windows (x64): Windows XP Professional for x64, Windows Vista* for x64, Windows 7** for x64
  • Microsoft Internet Explorer 8, Firefox, Chrome
Server Environment
  • HP-UX Itanium: HP-UX 11iv3 (11.31)
  • HP-UX PA-RISC: HP-UX 11iv3 (11.31)
  • IBM AIX: 6.1 and 7.1 (x64) on POWER architectures
  • Linux for x86 (x86-32): RHEL 5 and 6, SuSE SLES 10
  • Linux for x64 (EM64T/AMD64): RHEL 5 and 6, SuSE SLES 10 and 11
  • Microsoft Windows on x64 (EM64T/AMD64): Windows XP Professional for x64, Windows 7** for x64, Windows Server 2003 for x64, Windows Server 2008 for x64, Windows Vista* for x64
  • Solaris on SPARC: Version 10
  • Solaris on x64: Version 10

* NOTE: Windows Vista supported editions are Enterprise, Business and Ultimate.
** NOTE: Windows 7 supported editions are Professional, Enterprise and Ultimate.

Ready to learn more?

Call us at 1-800-727-0025 (US and Canada) or request more information.