Complex mechanisms exist between public risk perception, emotions, and coping behaviors during health emergencies. To unravel the relationship between these three phenomena, a meta-analytic approach was employed in this study. Using Comprehensive Meta-Analysis 3.0, 81 papers were analyzed after selection. The results of the meta-analysis showed that (1) risk perception (perceived severity, perceived susceptibility) and negative emotions (especially fear) are both correlated with coping behaviors; (2) risk perception is strongly correlated with fear and moderately correlated with anxiety; and (3) anxiety predicts the adoption of coping behaviors. The existing research provided an empirical basis for implementing effective coping behavior interventions and implied that management decisionmakers need to consider reasonable interventions through multiple channels to maintain the public’s risk perception and emotions within appropriate levels. Finally, future research directions are suggested.

Purpose: Due to the increasing demand for public services, as a new form of public governance, e-participation has emerged. Scholars from various disciplines have published plenty of research results on e-participation. This paper aims to reveal the research status frontiers directly by mapping knowledge domains. Design/methodology/approach: The authors take 1,322 articles on e-participation published in Web of Science from 2001 to 2017 as research object. They then run the information visualization software CiteSpace to drill deeper into the literature data. Findings: The study found that e-participation research has the obvious interdisciplinary feature; the author and institution cooperation networks with less internal cooperation are relatively sparse; the USA ranks first in the field of e-participation research, followed by the UK, with the other countries lagged behind; and e-participation through social media is gradually becoming the new research focus. Originality/value: Based on the objective data and information visualization technology, the research intuitively reveals the research status and development trend of e-participation.

The interactive information in blockchain architecture establishes an effective communication channel between users and enterprises, enabling them to communicate in a comprehensive and effective manner. Therefore, taking blockchain interactive information as the research object, this paper explores how the intervention of official information on investors affects the stock price movement and then makes predictions on stock prices according to the emotional tendency of interactive information. With the contextual information fusion, a sentiment computing model based on a convolutional neural network is established to extract and quantify the emotional features of blockchain interactive information. Combined with investors’ emotional features, the stock price prediction model based on long short-term memory is proposed. The experiment results show that the accuracy of the model has been improved by incorporating the intervened emotional features, thereby proving that information clarification can have a positive effect on the stock price.