Sarcasm Detection : Achilles Heel of sentiment analysis

schedule Aug 31st 02:00 PM - 02:45 PM place Neptune people 74 Interested

Sentiment analysis has been for long poster boy problem of NLP and has attracted a lot of research. However, despite so much work in this sub area, most sentiment analysis models fail miserably in handling sarcasm. Rise in usage of sentiment models for analysis social data has only exposed this gap further. Owing to the subtilty of language involved, sarcasm detection is not easy and has facinated NLP community.

Most attempts at sarcasm detection still depend on hand crafted features which are dataset specific. In this talk we see some of the very recent attempts to leverage recent advances in NLP for building generic models for sarcasm detection.

Key take aways:
+ Challenges in sarcasm detection
+ Deep dive into a end to end solution using DL to build generic models for sarcasm detection
+ Short comings and road forward

 
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Outline/structure of the Session

  • Introduction to sarcasm detection
    • Its importance
    • Why is it difficult
  • Introduction to known techniques to solve this problem
  • Leveraging Deep Learning to solve it
    • Why known DL ways dont work
    • What special needs to be done.
  • Solution:
    • CNNs for NLP
    • CNNs for Sarcasm detection
  • Short comings
  • Take home

Learning Outcome

  • Challenges in sarcasm detection.
  • State of art in sarcasm detection.
  • Deep dive into an end to end solution using DL to build generic models for sarcasm detection.
  • Shortcomings of present solution and road forward.

Target Audience

Practitioners working in the area of NLP, Deep Learning, Machine Learning.

schedule Submitted 6 months ago

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  • Naresh Jain
    By Naresh Jain  ~  5 months ago
    reply Reply

    Anuj, thank you for proposing this topic on Sarcasm Detection. I very much appreciate the tight focus and clear learning outcome from this proposal.

    However, from the proposal, it's not clear if you already have a solution for Sarcasm Detection, which is being used in production or you are still in the exploration phase. 

    Also, can you please share what kind of use-cases have you applied this for and what is the general success rate you've found so far?

    Thank you!

    • Anuj Gupta
      By Anuj Gupta  ~  5 months ago
      reply Reply

      @Naresh Jain @Sohan Maheshwar: yes there are solution(s) 

      This is being used to detect sarcasm on twitter. I plan to cover this in depth in my talk 

    • Sohan Maheshwar
      By Sohan Maheshwar  ~  5 months ago
      reply Reply

      +1 to Naresh's questions. Interesting topic but would like clarity on whether there is a solution for sarcasm detection and what the success rate is.


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