Multimodal Analysis of the Public Opinion Response Discourse on Government New Media
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Abstract
Introduction: In the era of "Internet +," government new media plays an indispensable role in guiding positive public opinion. Despite the implementation of China’s Double Reduction policy, some local governments' responses to public opinion still need improvement. This study aimed to investigate the characteristics and patterns of the verbal and visual modes in public opinion response discourse on government new media and provide suggestions for these platforms to handle public events more effectively.
Methodology: This study was conducted using multimodal analysis of 68 microblogs responding to the Double Reduction policy from the official Weibo of People’s Daily, Xinhua News Agency and CCTV News. Based on the systemic functional grammar and visual grammar, this research explored the verbal mode in terms of ideational, interpersonal and textual metafunctions and the visual mode in terms of the representational, interactive and compositional meanings of government new media discourse.
Results: The findings indicated that verbal response from government new media mainly consisted of heading, hashtags and texts, and the visual includes images and videos. The visual mode was in line with the verbal mode to respond to public concerns at issue. The information conveyed was strengthened by the application of images or complemented by the images.
Conclusion: This study contributes to establishing the image of government authority. By capturing the potential meaning of verbal and visual modes, this study also provides some suggestions for improving the discourse quality of government new media when responding to public events.
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