1 Introduction

Social media provides a new channel for telling Chinese stories, but there are communication challenges. This study analyzes the characteristics of anti epidemic tweets from three dimensions: relational behavior, information participation quality, and language features, and explores their impact on the behavioral participation of overseas audiences, aiming to enhance the international dissemination effect of Chinese stories.

2 Literature Review

The literature review section explores the five basic elements of the communication process, namely the "5W model", and points out that foreign researchers' attention to the effectiveness of social media communication mainly focuses on health communication, public life participation, and influencing factors. Domestic research focuses on the dissemination effects of social media platforms such as WeChat and Weibo, but there is relatively little research on overseas social media. There are shortcomings in evaluating the effectiveness of communication in telling Chinese stories to the outside world, including insufficient empirical research, single themes, and insufficient attention to overseas social media. This study aims to combine the perspectives of communication and linguistics to analyze the textual characteristics of Chinese anti epidemic tweets from multiple dimensions and their impact on overseas dissemination effects.

A multidimensional analysis framework for the characteristics of three tweets

This chapter constructs a multidimensional analysis framework for the characteristics of tweets, covering three levels: macro, meso, and micro. At the macro level, attention is paid to relational behavior, and based on the theory of speech acts, tweets are divided into two categories: propaganda and interpersonal relationship construction. Mid level analysis of information participation quality, including interactivity and media richness, affects user perception and behavior. Exploring language features at a micro level, using LIWC tool to analyze lexical grammatical features of tweets.

4 Research Design

This chapter elaborates on the research design of the impact of the characteristics of Chinese anti epidemic tweets on the behavioral participation of overseas audiences. The research focuses on the relationship behavior, information participation quality, language expression characteristics, and their impact on the behavioral participation of overseas audiences in Chinese anti epidemic tweets, and explores the predictive power of these text features. The study collected COVID-19 related tweets from five mainstream Chinese media outlets on Twitter and constructed a corpus of 2500 tweets. The research tool uses LIWC to analyze the language features of tweets, covering multiple dimensions. In the data analysis section, the study examined the relationship between text features and overseas audience behavior participation through methods such as one-way ANOVA, Spearman correlation analysis, and Pearson correlation analysis, and conducted multiple linear regression analysis to explore the predictive power of text features.

5 Results and Discussion

Analyzed the relationship between Chinese anti epidemic tweets and overseas audience behavior participation. Research has found that the relationship behavior of tweets includes five categories: disclosure, promotion, demand, expression, and sharing. Among them, promotion and disclosure have the highest number of tweets and the highest audience engagement. The interactivity and diversity of tweets are moderately and weakly correlated with audience engagement, indicating that interactivity and content diversity enhance audience willingness to participate. Language feature analysis shows that present tense words, adverbs, binary thinking words, emotional tone, and social referents are positively correlated with audience engagement, while internet language words, analytical thinking words, and negative emotions are negatively correlated with audience engagement. Multiple linear regression analysis shows that text interactivity, binary thinking words, future tense words, adverbs, anxiety words, and attention words can explain 25.2% of the variation in audience behavior participation, with text interactivity features having the greatest predictive effect on audience participation.

6 Conclusion

This study analyzed the textual features of Chinese anti epidemic tweets and their impact on the behavioral engagement of overseas audiences. On a macro level, diversified communication themes such as vaccine research and development, foreign aid, etc. can increase participation, while sharing and expression of analogies need to be optimized. At the meso level, the interactivity and diversity of tweets are significantly correlated with engagement, but most tweets lack interactivity. At the micro level, 44 language features are related to participation, of which 6 variables can explain 25.2% of the variation. Research suggests that the dissemination of Chinese stories should seize promotional opportunities, set diverse themes, optimize content and form, consider audience language habits, establish connections, provide timely feedback, and adopt a plain and friendly narrative style to enhance audience trust and emotional identification. The limitation of the study is that it did not consider the emotional attitudes of the audience. Future research can comprehensively understand the impact of tweet features on communication effectiveness by analyzing audience comments.