The document discusses mining Facebook data to analyze feelings. It finds over 100,000 instances each of "happy" and "proud" feelings. Machine learning classifiers were able to accurately classify feelings into basic categories like joy, anger, fear with up to 87% accuracy. The classifiers also classified feelings in terms of arousal and valence, or positive and negative feelings. A test set of Facebook data was manually assessed to check if automated classification of feelings matched how human coders interpreted the expressed feelings, with agreement of around 80% between coders and the automated system.

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