Start Date
12-16-2013
Description
Depression is one of the most common mental health problems among young adults, which is often associated with many other negative health and social problems. Despite numerous studies about depression and its transmission in the offline environment, there are few studies investigating how depression is transmitted on Social Network Sites (SNS). In this study, we build a new theory about depression contagion on SNS. We propose that negative (positive) contents can enhance (attenuate) users’ depression levels. Furthermore, two factors: communication specificity and tie strength are expected to moderate the relationship between content valence and depression level. We use sentiment analysis to measure content valence, and design a novel mixed approach to measure users’ depression symptoms and moods. The results of the study will help us find some methods to alleviate depression that may occur via communication on SNS.
Recommended Citation
Xu, Haifeng; Phan, Tuan Quang; and Tan, Bernard, "How Does Online Social Network Change My Mood? An Empirical Study of Depression Contagion On Social Network Sites Using Text-mining" (2013). ICIS 2013 Proceedings. 44.
https://aisel.aisnet.org/icis2013/proceedings/ResearchInProgress/44
How Does Online Social Network Change My Mood? An Empirical Study of Depression Contagion On Social Network Sites Using Text-mining
Depression is one of the most common mental health problems among young adults, which is often associated with many other negative health and social problems. Despite numerous studies about depression and its transmission in the offline environment, there are few studies investigating how depression is transmitted on Social Network Sites (SNS). In this study, we build a new theory about depression contagion on SNS. We propose that negative (positive) contents can enhance (attenuate) users’ depression levels. Furthermore, two factors: communication specificity and tie strength are expected to moderate the relationship between content valence and depression level. We use sentiment analysis to measure content valence, and design a novel mixed approach to measure users’ depression symptoms and moods. The results of the study will help us find some methods to alleviate depression that may occur via communication on SNS.