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Sentiment Analysis Symposium2014

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1. Sharing Emotions in Social Networks Data Mining Tools for Audience Sentiment Analysis Sentiment Symposium 2014 5/3/2014 – New York City Vittorio Di Tomaso @CELI_NLP

2. Blogmeter collects 1M+ Italian tweets every day About 10% are related to TV programs Second screen is a reality All data collected using BlogMeter’s SocialTVMeter

3. The Experiment Is it possible to give broadcasters and advertisers true insights on how programs are perceived by their audiences?

4. What we want A methodology to discover meaningful similarities and differences in a collection of items described by several variables (sentiment & emotions)

5. Semantic Analysis Sentiment analysis: positive and negative tweets Emotion detection: anger, disgust, fear, joy, sadness, surprise, love, like, dislike

6. The result of semantic analysis

7. Data Analysis: can we do better? To gain a deeper understanding of data, we derived a geometric representation of people AND emotions in the same space We employed Multiple Correspondence Analysis, a PCA variant for discrete data

8. COMPARING PROGRAMS’ EMOTIONAL SPECTRA

9. Simple CA: TV Shows and Classification 9 Emotions & Programs Multiple Correspondence Analysis ©Copyright Celi/Blogmeter 2014

10. COMPARING X-FACTOR AND MASTERCHEF’S EMOTIONAL SPECTRA

11. X Factor 7 Correspondences between Episodes and Emotions ©Copyright Celi/Blogmeter 2014

12. MasterChef Correspondences between Episodes and Emotions ©Copyright Celi/Blogmeter 2014

13. X Factor vs Masterchef ©Copyright Celi/Blogmeter 2014

14. Conclusions Multivariate techniques were succefully applied on high quality semantic data Highlighting relevant features of audiences provides crucial pieces of information to broadcasters and potential advertisers

15. Thanks! Vittorio Di Tomaso ditomaso@celi.it Francesco Tarasconi tarasconi@celi.it www.celi.it www.blogmeter.it

Publié dans : Technologie, Formation
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Sentiment Analysis Symposium2014

  1. 1. Sharing Emotions in Social Networks! Data Mining Tools for Audience Sentiment Analysis! ! Vittorio Di Tomaso! ! 1!
  2. 2. ! Blogmeter collects 1M+ Italian tweets every day! ! About 10% are related to TV programs! ! Second screen is a reality! All  data  collected  using  BlogMeter’s  SocialTVMeter   2!
  3. 3. The Experiment !! Is it possible to give broadcasters and advertisers true insights on how programs are perceived by their audiences?! 3!
  4. 4. What we want! A methodology to discover meaningful similarities and differences in a collection of items described by several variables (sentiment & emotions)! 4!
  5. 5. Semantic Analysis! Sentiment analysis:! positive and negative tweets! ! Emotion detection:! anger, disgust, fear, joy, sadness, surprise, love, like, dislike! 5!
  6. 6. The result of semantic analysis! 6!
  7. 7. Data Analysis: can we do better?! To gain a deeper understanding of data, we derived a geometric representation of people AND emotions in the same space! ! We employed Multiple Correspondence Analysis, a PCA variant for discrete data! 7!
  8. 8. COMPARING PROGRAMS’ EMOTIONAL SPECTRA! 8!
  9. 9. Simple CA: TV Shows and Classification! 9! Emotions & Programs! Multiple Correspondence Analysis! ©Copyright  Celi/Blogmeter  2014  
  10. 10. 10! COMPARING X-FACTOR AND MASTERCHEF’S EMOTIONAL SPECTRA!
  11. 11. 11! X Factor 7! Correspondences between Episodes and Emotions! ©Copyright  Celi/Blogmeter  2014  
  12. 12. MasterChef! Correspondences between Episodes and Emotions! ©Copyright  Celi/Blogmeter  2014  
  13. 13. 13! X Factor vs Masterchef! ©Copyright  Celi/Blogmeter  2014  
  14. 14. Conclusions! Multivariate techniques were succefully applied on high quality semantic data! ! Highlighting relevant features of audiences provides crucial pieces of information to broadcasters and potential advertisers! 14!
  15. 15. Thanks!! Vittorio Di Tomaso ! ditomaso@celi.it! Francesco Tarasconi! tarasconi@celi.it! www.celi.it! www.blogmeter.it! 15!

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