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.