IJCAI-13 Sentiment Analysis Tutorial (Beijing, China)

Tutorial Description

Sentiment analysis (or opinion mining) is defined as the task of finding the opinions of authors about specific entities. The decision making process of people is affected by the opinions formed by thought leaders and ordinary people. When a person wants to buy a product online he or she will typically start by searching for reviews and opinions written by other people on the various offerings. Sentiment analysis is one of the hottest research areas in computer science. Over 7,000 articles have been written on the topic. Hundreds of startups are developing sentiment analysis solutions and major statistical packages include dedicated sentiment analysis modules. There is a huge explosion today of texts available from social media including Twitter, Facebook, message boards, blogs, and user forums. These snippets of text are a gold mine for companies and individuals that want to monitor their reputation and get timely feedback about their products and actions. Sentiment analysis offers these organizations the ability to monitor the different social media sites in real time and act accordingly. Marketing managers, PR firms, campaign managers, politicians and even equity investors and online shoppers are the direct beneficiaries of sentiment analysis technology.

Tutorial Outline

  1. Introduction to Sentiment Analysis
    • what is sentiment analysis?
    • who needs it and why is it useful?
    • what kinds of fields is it used in?
    • how successful is sentiment analysis in prediction?
  2. Building Sentiment Analysis Systems
    • sentiment analysis at the document, sentence, and aspect level
    • sentiment lexicon acquisition
    • opinion holder identification
    • trustworthy opinions, spam opinions, and fake reviews
    • detecting and dealing with complications: sarcasm/irony, negation, and slang and incorrect English
    • strengths and weaknesses of current systems: available tools and how to compare and evaluate the different types (commercial, research, public)
  3. Applications
    • Sentiment in Financial News
      • a detailed description of a financial sentiment analysis system
      • step by step description of a real application for analyzing Stock Twits
    • Brand Monitoring and Marketing
      • analyzing user forums
      • step by step description of a real application for analyzing social media (Twitter, Facebook and Google+) for general opinions about products, brands, people etc.
      • discussion of, and solutions to, the challenges imposed by processing social media (use of incorrect language, short or incomplete sentences, lack of contextual information, use of multiple languages, etc., use of slang, etc.)
  4. Summary and Q+AImage

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