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The online peer-to-peer healthcare communities are known as the platform where dispersed groups of patients and their families query information, seek and offer support, and connect with others. The success of such communities relies on users’ ongoing involvement to generate benefits for both individuals and the communities. This study attempts to understand users’ continuance participation in online peer-to-peer healthcare community by classifying users’ goals of participation based on the user-generated text contents. We proposed a rule-based classification framework to categorize users’ goals of posting contents into four categories: information seeking, experience sharing, information sharing, and social interaction. We formalize and test the relationship between users’ continuance participation and all four posting goals, and find that the first three goals have significant impact on users’ continuance participation. Our findings can help researchers and practitioners better understand users’ behavior in the online peer-to-peer healthcare community.

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Users’ Continuance Participation in the Online Peer-to-peer Healthcare Community: A Text Mining Approach

The online peer-to-peer healthcare communities are known as the platform where dispersed groups of patients and their families query information, seek and offer support, and connect with others. The success of such communities relies on users’ ongoing involvement to generate benefits for both individuals and the communities. This study attempts to understand users’ continuance participation in online peer-to-peer healthcare community by classifying users’ goals of participation based on the user-generated text contents. We proposed a rule-based classification framework to categorize users’ goals of posting contents into four categories: information seeking, experience sharing, information sharing, and social interaction. We formalize and test the relationship between users’ continuance participation and all four posting goals, and find that the first three goals have significant impact on users’ continuance participation. Our findings can help researchers and practitioners better understand users’ behavior in the online peer-to-peer healthcare community.