sentiment analysis symposium2014

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Sharing Emotions in Social Networks Data Mining Tools for Audience Sentiment Analysis Vittorio Di Tomaso 1

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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 [email protected] Francesco Tarasconi [email protected] www.celi.it www.blogmeter.it

TRANSCRIPT

Page 1: Sentiment Analysis Symposium2014

Sharing Emotions in Social Networks!Data Mining Tools for Audience Sentiment Analysis!!Vittorio Di Tomaso!

!

1!

Page 2: Sentiment Analysis Symposium2014

!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!

Page 3: Sentiment Analysis Symposium2014

The Experiment !!

Is it possible to give broadcasters and advertisers true insights on how programs are perceived by

their audiences?!

3!

Page 4: Sentiment Analysis Symposium2014

What we want!

A methodology to discover meaningful similarities and

differences in a collection of items described by several variables

(sentiment & emotions)!

4!

Page 5: Sentiment Analysis Symposium2014

Semantic Analysis!

Sentiment analysis:!positive and negative tweets!

!Emotion detection:!

anger, disgust, fear, joy, sadness, surprise, love, like, dislike!

5!

Page 6: Sentiment Analysis Symposium2014

The result of semantic analysis!

6!

Page 7: Sentiment Analysis Symposium2014

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!

Page 8: Sentiment Analysis Symposium2014

COMPARING PROGRAMS’ EMOTIONAL SPECTRA!

8!

Page 9: Sentiment Analysis Symposium2014

Simple CA: TV Shows and Classification!

9!

Emotions & Programs!Multiple Correspondence Analysis!

©Copyright  Celi/Blogmeter  2014  

Page 10: Sentiment Analysis Symposium2014

10!

COMPARING X-FACTOR AND MASTERCHEF’S EMOTIONAL SPECTRA!

Page 11: Sentiment Analysis Symposium2014

11!

X Factor 7!Correspondences between Episodes and Emotions!

©Copyright  Celi/Blogmeter  2014  

Page 12: Sentiment Analysis Symposium2014

MasterChef!Correspondences between Episodes and Emotions!

©Copyright  Celi/Blogmeter  2014  

Page 13: Sentiment Analysis Symposium2014

13!

X Factor vs Masterchef!

©Copyright  Celi/Blogmeter  2014  

Page 14: Sentiment Analysis Symposium2014

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!

Page 15: Sentiment Analysis Symposium2014

Thanks!!

Vittorio Di Tomaso [email protected]!Francesco [email protected]!www.celi.it!www.blogmeter.it!

15!