Leader identification in an online health community for cancer survivors: a social network-based classification approach

Online health communities (OHCs) are an important source of social support for cancer survivors and their informal caregivers. This research attempted to identify leaders in a popular online forum for cancer survivors and caregivers using classification techniques. We first extracted user features from many different perspectives, including contributions, network centralities, and linguistic features. Based on these features, we leveraged the structure of the social network among users and generated new neighborhood-based and cluster-based features. Classification results revealed that these features are discriminative for leader identification. Using these features, we developed a hybrid approach based on an ensemble classifier that performs better than many traditional metrics. This research has implications for understanding and managing OHCs.