Perceived Usefulness of Online Health Information Sharing: A Text Mining Based Empirical Research.

Due to the concern for time and geological distance, the seeking health information behavior of patients has transferred from offline to online. The online information sharing has become one of the main sources where patients can obtain health information. Thus, the usefulness of online health information sharing is particularly important. This paper collects 9902 articles in health field from Baidu Experience which is the largest experience-sharing platform in China. It adopts the Information Adoption Model to analyze the impact of author’s credibility, text attributes, and pictures on the perceived usefulness of health-information-sharing articles. Results show that readers prefer long articles with more detailed health information and negative emotions in articles can affect readers’ perception of usefulness. And illustrated articles are easier to receive recognition. On the other hand, authors’ motivation in utilitarianism may lead to challenges to quality of the health-information-sharing article and, in return, hinder readers from adopt the information from the article.