An emotional feedback system based on a regulation process model for happiness improvement

In this paper, an integrated emotion regulation system (IERS) is proposed based on the regulation process model for happiness improvement. Including extracting the valuable information from user´s contents on social network, the IERS analyzes users´ emotion variation and semanteme reflecting to the regulation process model and aim to appropriately feedback to users. The feedback sentences are chosen from regulation corpus which is positive and motivated. The proposed IERS works at the word level and the emotional topics is classified by SVM through the corpus collected from Facebook wall, whereas feedback strategy sentences is chosen through Point-Wise Mutual Information (PMI) features. The accuracy result of seven-type emotion recognition can achieve higher than 50%. The pre- and post-experiment results are evaluated by 20 participants in one week of observation, of which the result implies the proposed system can practically improve the happiness.