What health-related information flows through you every day? A content analysis of microblog messages on air pollution

How Social Media Exposure to Health Information Influences Chinese People's Health Protective Behavior during Air Pollution: A Theory of Planned Behavior Perspective

Haze has become one of the most life-threatening problems in China and affects over one billion Chinese people's health. Chinese people have become more dependent on receiving health information from social media, especially Weibo and WeChat, which shapes their health perceptions and behaviors. To investigate how Chinese people's exposure to health information on social media influenced their health protective behaviors in response to haze, particularly wearing a PM2.5 anti-haze mask, we conducted a longitudinal web-based survey of mainland Chinese. The results from the structural equation modeling showed that (a) attitude and descriptive norm positively mediated the relationships between using Weibo for health information and behavioral intention while descriptive norm negatively mediated the relationship between using WeChat for health information and intention, and that (b) attitude, descriptive norm, and injunctive norm significantly predicted behavioral intention and wearing mask, but perceived behavior control did not. Theoretical and practical implications are discussed.

Can the adoption of health information on social media be predicted by information characteristics?

Purpose

This paper aims to explore the relationship between the characteristics of social media health information and its adoption. The purpose is to identify information characteristics that can be used to estimate the level of health information adoption in advance.

Design/methodology/approach

According to the Information Adoption Model (IAM), the study extracted ten information characteristics from the aspects of information quality and information source credibility. The sample data was collected from the top ten influential health accounts based on the Impact List of Sina Weibo to test the effectiveness of these characteristics in distinguishing information at different levels of adoption. The forecasting of information adoption level is regarded as a binary classification question in the study and support vector machine (SVM) is used to do the research.

Findings

The results indicate that ten information characteristics chosen in this study are related to information adoption. Based on these information characteristics, it is feasible to estimate the level of health information adoption, and the estimation accuracy is relatively high.

Originality/value

A lot of work has been done in previous researches to reveal the factors that influence information adoption. The theoretical contribution of this work is to further discuss how to use the influencing factors to do some predictive work for information adoption. In practice, it will help health information publishers to disseminate high-quality health information more effectively as well as promote the adoption of health information.

Exploring Environmental Health on Weibo: A Textual Analysis of Framing Haze-Related Stories on Chinese Social Media

According to the latest report by the World Health Organization, air pollution, one of the planet’s most dangerous environmental carcinogens, has become one of the leading causes of cancer-related deaths. In China this is a particularly crucial issue, with more than 100 cities and close to one billion individuals threatened by haze due to heavy air pollution in recent years. Beyond traditional channels, the rise of social media has led to greater online haze-related information sharing. Formative research suggests that Weibo is playing a larger role in the process of information seeking than traditional media. Given the severity of haze and the influential role of Weibo, a textual analysis was conducted based on Sina Weibo (Chinese Twitter) to provide health decision-makers and media consumers knowledge on how environmental health issues such as haze are framed in Chinese social media. Framing theory served to explain the differences across various outlets: People’s Daily, China Daily, and the Chinese version of the Wall Street Journal. By analyzing 407 Weibo posts, five major frames emerged: (1) governmental concern, (2) public opinion and issue management, (3) contributing factors and effects, (4) socializing haze-related news, and (5) external haze-related news.