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

AnimatedExcited 155291Pumped 2979Surprised 752Amused 14993

JoyHappy 114259Wonderful 54691Awesome 22351Super 5794Great 55180Fantastic 3596Delighted 805Satisfied 1349Content 628Hopeful 21399

AngryAngry 12680Pissed 3851Annoyed 16839Frustrated 1145Disappointed 2534Disgusted 1566

FearfulWorried 3274Scared 2075Anxious 1002Shocked 1391Confused 3904

EmpoweredDetermined 29850Confident 2341Accomplished 6570Proud 31363

Daniel Hardt Mining Facebook for Feelings

Classifier

Basic Feelings (5-way classification)Classifier: MaxEntTraining Accuracy: .87Testing Accuracy: .75 (10-fold validation)

Arousal (2-way classification)Classifier: MaxEntTraining Accuracy: .99Testing Accuracy: .80 (10-fold validation)

Valence (2-way classification)Classifier: MaxEntTraining Accuracy: .99Testing 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 sourcesManual Task: Order Feelings Expressed (1 is mostexpressed, 5 least; 0 not expressed at all)Results: Binary Decision – is feeling expressed or not?

(Ignore examples where 1st coder notes no feelingsexpressed – leaves 92 examples)Agreement on Feelings Expressed1st coder vs 2nd coder: 0.797385620915033 366 out of459 in 92 cases1st coder vs System: 0.734204793028322 337 out of 459in 92 cases

Daniel Hardt Mining Facebook for Feelings