Stress has become an important health issue with the rapid development of economy and society. The previous work has highlighted the discriminatory power of Electrocardiogram (ECG) and social media for stress detection. However, limitations exist when using single source data for stress detection. Based on the assumption that abnormal heart rate periods are usually caused by stressor or uplifting events, we present a way to integrate heart beat rates and linguistic posts on microblogs for stress detection. We first identify one's abnormal heart rate periods, and then for each such period, we p...
