Practical Sentiment Analysis

Prof. Ronen Feldman‘s 3-hour “State of the Art Sentiment Analysis” tutorial will be followed by a half-hour session on “Sentiment Analysis Solutions” presented by industry analyst and consultant Seth Grimes. The sessions are designed for practitioners, developers, and managers who seek a comprehensive and concise introduction to techniques and applications. They will run from 8:30 am to 12:30 pm on April 2, 2019.

State of the Art Sentiment Analysis: Outline

  1. Introduction: What is Sentiment Analysis and why is it hard?
    1. Uses of sentiment analysis
    2. Different types of sentiment analysis
  2. Sentiment analysis and Information Extraction (IE)
    1. Why sentiment analysis requires IE
    2. The core components of IE Systems
      1. entity recognition
      2. Anaphora resolution
      3. relationship extraction
  3. Sentiment Analysis (SA)
    1. Sentiment analysis types and uses
      1. Kinds of sentiment
      2. Polarity, intensity and subjectivity
    2. Sentiment Granularity
      1. Document Sentiment Classification
      2. Sentence Subjectivity and Sentiment Classification
      3. Aspect Sentiment Classification
      4. Aspect and Entity Extraction
    3. Approaches to sentiment analysis
      1. Dictionary-based
      2. Pattern-based
      3. Event-based
    4. Machine learning methods for sentiment analysis
      1. Unsupervised
      2. Supervised
      3. Semi-supervied
      4. Deep Learning
    5. Analysis of Comparative Opinions
    6. Opinion Summarization and Visualization
  4. Sentiment Analysis in Social Networks
    1. Challenges of Sentiment Analysis in Social Networks
    2. Sentiment Analysis of Product reviews
      1. Quality of Reviews
    3. Opinion Spam Detection in Social Networks
    4. Irony, Sarcasm
    5. Opinion Leader Detection
    6. Deep Analysis of Debates and Comments
    7. Mining Intentions
    8. Detecting Fake or Deceptive Opinions
  5. Detailed sentiment analysis case studies:
    1. Discussion Boards
      1. Extracting product comparisons
      2. Assessing market structure
    2. Medical Forums
      1. How users feel about various drugs?
      2. When do they switch to other drugs and why?
      3. Predicting FDA actions based on medical forums analysis
    3. Facebook
      1. predicting user personality and happiness
    4. Scientific and technological texts
      1. sentiment about emerging technologies
      2. predicting successful and failing products
    5. Social and mainstream news media
      1. Extracting sentiment about stocks and companies, applications for hedge funds and banks.
      2. How can Sales reps utilize the sentiment about their prospective companies
  6. Conclusions
    1. What works when
    2. Resources for sentiment analysis
      1. Sentiment dictionaries
      2. Corpora
    3. Emerging industry and research directions

Sentiment Analysis Solutions

This 30-minute workshop presentation will survey the sentiment analysis market and solutions, complementing Prof. Feldman’s tutorial. It will cover products and services designed for business users, data scientists, and developers in domains that include customer experience, market research, media, and finance, also online and social media and conversational interfaces. 

 

 

 

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