Tutorial, March 26 State of the Art Sentiment Analysis: Techniques and Applications

Prof. Ronen Feldman will offer a half-day tutorial on Monday afternoon, March 26, 1:30 pm to 5 pm. The “State of the Art Sentiment Analysis” tutorial is designed for practitioners, developers, and managers who seek a comprehensive and concise introduction to techniques and applications. Prof. Feldman is a text analytics pioneer.


    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

Symposium day 2 will feature conference presentations and panels. Attend either day or both, but whichever day(s) you attend, join us for a networking reception Tuesday evening, March 27, 5:30-7 pm!





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