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Mining Facebook for Feelings
Daniel Hardt
Copenhagen Business School
9 June 2015
Daniel Hardt Mining Facebook for Feelings
Data: Facebook Feelings
Daniel Hardt Mining Facebook for Feelings
Arousal and Valence: Data
Daniel Hardt Mining Facebook for Feelings
Five Basic Feelings: Data
Animated
Excited 155291
Pumped 2979
Surprised 752
Amused 14993
Joy
Happy 114259
Wonderful 54691
Awesome 22351
Super 5794
Great 55180
Fantastic 3596
Delighted 805
Satisfied 1349
Content 628
Hopeful 21399
Angry
Angry 12680
Pissed 3851
Annoyed 16839
Frustrated 1145
Disappointed 2534
Disgusted 1566
Fearful
Worried 3274
Scared 2075
Anxious 1002
Shocked 1391
Confused 3904
Empowered
Determined 29850
Confident 2341
Accomplished 6570
Proud 31363
Daniel Hardt Mining Facebook for Feelings
Classifier
Basic Feelings (5-way classification)
Classifier: MaxEnt
Training Accuracy: .87
Testing Accuracy: .75 (10-fold validation)
Arousal (2-way classification)
Classifier: MaxEnt
Training Accuracy: .99
Testing Accuracy: .80 (10-fold validation)
Valence (2-way classification)
Classifier: MaxEnt
Training Accuracy: .99
Testing Accuracy: .83 (10-fold validation)
Daniel Hardt Mining Facebook for Feelings
Two-D Classification: Valence and Arousal
Daniel Hardt Mining Facebook for Feelings
Two-D Classification: Comparisons
Daniel Hardt Mining Facebook for Feelings
Feeling Meter: Manual Assessment
Test Set: 160 examples from different sources
Manual Task: Order Feelings Expressed (1 is most
expressed, 5 least; 0 not expressed at all)
Results: Binary Decision – is feeling expressed or not?
(Ignore examples where 1st coder notes no feelings
expressed – leaves 92 examples)
Agreement on Feelings Expressed
1st coder vs 2nd coder: 0.797385620915033 366 out of
459 in 92 cases
1st coder vs System: 0.734204793028322 337 out of 459
in 92 cases
Daniel Hardt Mining Facebook for Feelings

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Mining Facebook for Feelings

  • 1. Mining Facebook for Feelings Daniel Hardt Copenhagen Business School 9 June 2015 Daniel Hardt Mining Facebook for Feelings
  • 2. Data: Facebook Feelings Daniel Hardt Mining Facebook for Feelings
  • 3. Arousal and Valence: Data Daniel Hardt Mining Facebook for Feelings
  • 4. Five Basic Feelings: Data Animated Excited 155291 Pumped 2979 Surprised 752 Amused 14993 Joy Happy 114259 Wonderful 54691 Awesome 22351 Super 5794 Great 55180 Fantastic 3596 Delighted 805 Satisfied 1349 Content 628 Hopeful 21399 Angry Angry 12680 Pissed 3851 Annoyed 16839 Frustrated 1145 Disappointed 2534 Disgusted 1566 Fearful Worried 3274 Scared 2075 Anxious 1002 Shocked 1391 Confused 3904 Empowered Determined 29850 Confident 2341 Accomplished 6570 Proud 31363 Daniel Hardt Mining Facebook for Feelings
  • 5. Classifier Basic Feelings (5-way classification) Classifier: MaxEnt Training Accuracy: .87 Testing Accuracy: .75 (10-fold validation) Arousal (2-way classification) Classifier: MaxEnt Training Accuracy: .99 Testing Accuracy: .80 (10-fold validation) Valence (2-way classification) Classifier: MaxEnt Training Accuracy: .99 Testing Accuracy: .83 (10-fold validation) Daniel Hardt Mining Facebook for Feelings
  • 6. Two-D Classification: Valence and Arousal Daniel Hardt Mining Facebook for Feelings
  • 7. Two-D Classification: Comparisons Daniel Hardt Mining Facebook for Feelings
  • 8. Feeling Meter: Manual Assessment Test Set: 160 examples from different sources Manual Task: Order Feelings Expressed (1 is most expressed, 5 least; 0 not expressed at all) Results: Binary Decision – is feeling expressed or not? (Ignore examples where 1st coder notes no feelings expressed – leaves 92 examples) Agreement on Feelings Expressed 1st coder vs 2nd coder: 0.797385620915033 366 out of 459 in 92 cases 1st coder vs System: 0.734204793028322 337 out of 459 in 92 cases Daniel Hardt Mining Facebook for Feelings