Negative energy detector using cellphone bluetooth and contact list

Abstract

Individual mood is important for physical and emotional well-being. Despite the physiological reasons, emotional contagion between peoples is also pivotal to understand and further predict people's emotional change. However, an ignored yet important task is to find the behavior differences between easygoing and sharp-tongued persons in daily life. We present a novel metric to measure people's capacity to make their encounters negative. Then Latent Dirichlet Allocation topic model and multimodal exposure features(MME) are used to study the behavior differences, extracting the probable contact patterns of different kinds of people and how they contact with each other. Finally, to make practical, a MME Feed-forward Neural Network is given out to judge people's role in emotion contamination, with using people's own mobile-phones contact list. Taking the MIT Social Evolution dataset as an example, the experimental results verify the efficacy of our techniques on real-world data.