This study focused on an online knowledge-sharing community, in which information was exchanged and accumulated actively in the community based on the question-and-answer interaction of users. We examined its characteristics by text mining, one of the most effective methods for the content analysis of enormous quantities of text-based data. Based on an analysis of posted questions and answers, the same gender difference as in previous studies on interpersonal communicative discourse was found. Female users tended to post questions and answers related to their interpersonal relationships. Based on an analysis of their perspectives on the community, it was suggested that many users positively evaluated the usefulness of the community and did not hesitate to post questions and answers. These attitudes of users toward the community should lead to their positive evaluation of both the overall community and the communication made there, as pointed out by Miura and Kawaura (2008).