Abstract

Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with those who face similar problems and are involved in different types of social supports, such as information support, emotional support and companionship. Using a case study of an OHC among breast cancer survivors, we first use machine learning techniques to reveal the types of social support embedded in each post from an OHC. Then we generate each user’s contribution profile by aggregating the user’s involvement in different types of social support and reveal the role the user plays in an OHC. By comparing online activities for users with different roles, we illustrate that users’ involvement in various types of social support is related to their level of engagement in an OHC.

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