This study explored the relationships between media exposure, cancer beliefs, and cancer information-seeking or information-avoidance behaviors. Based on the planned risk information-seeking model and its extended framework, two predictive models were constructed: one for cancer information seeking and the other for cancer information avoidance. A structural equation modeling strategy was applied to survey data from China HINTS 2017 (n = 3090) to compare the impact of traditional mass media and social media exposure to cancer-related information on cancer information-seeking and information-avoidance behaviors. The study findings suggest that health-related information exposure through different media channels may generate distinctive information-seeking or information-avoidance behaviors based on various cancer beliefs. Additionally, the findings indicate that social media exposure to health-related and cancer curability beliefs does not lead to cancer information avoidance; both mass media and social media exposure encourage people to seek cancer-related information. Cancer fatalism is positively associated with cancer information-seeking and avoiding intentions, suggesting that negative cancer beliefs predict seemingly contradictory yet psychologically coherent information intentions and behaviors.
Enabled by social media, the data frenzy in the data-driven fandom culture in China has attracted widespread attention. Unlike most forms of data labor and fan activities, Chinese fans’ online data-making behavior ( zuoshuju) appears tedious, time- and money-consuming, and overwhelmingly irrational. Therefore, this study aimed to examine the sociopsychological motivation of fans’ online data-making behavior from a collective action perspective. Based on survey data from 588 respondents with fandom experiences online in China, this study (1) distinguished two types of online data-making (operational and monetary); (2) suggested that celebrity worship and civic engagement intention were antecedents of online data-making; and (3) found that fan communities facilitated by social media bridged the effects of sociopsychological factors and data-making behavior. This research introduced the collective action perspective and constructed a quantitative path model to test the underlying mechanism and impetus of fans’ data-making practices in China, adding quantitative support to the knowledge of the hybrid pattern of collective actions embedded in the datafication world. It contributes to the understanding of Chinese youth culture and civic engagement through social media.
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