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This study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.

The authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.

The empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.

The results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.

Cyberbullying is a globally pervasive problem and not novel in academia. Previous studies mainly focussed on the features, consequences and technological management of cyberbullying. However, most of the studies took cyberbullying examples in the West, and some issues still need to be addressed in the Chinese context. Thus, this study investigates how participants use cyberbullying words and why they use them in that particular way in China.

This study uses content analysis to summarise the typical features of cyberbullying words, revealing a positive relationship between cyberbullying words and sentimental expressions. This paper also uses the questionnaire (N = 705) to explore the prevalence of cyberbullying among Chinese Internet users and to compare the gender differences in the cognition of cyberbullying words and involvement in cyberbullying, in line with the social cognitive theory.

This study stated that people prefer repetitively using offensive words to achieve cyberbullying goals. Interestingly, this study does not find obvious gender differences in cyberbullying roles and cyberbullying language use. However, it explained the relationship between cognition and the use of cyberbullying words from a gender perspective.

Theoretically, this study expands cyberbullying studies into a new cultural environment, pointing to a novel term, “imbalanced relation,” for exploring cyberbullying behaviours. This study highlights the significance of technology and education in detecting and preventing cyberbullying, suggesting that educators and social media platforms can directly predict and prevent cyberbullying through textual perspectives and individuals' cognition of cyberbullying.

This study aims to examine cyberbullying linguistic and emotional features and individual differences in cyberbullying behaviour in a high-context culture like China. Its values include comparing the differences between cyberbullying in China and cyberbullying in the West from the linguistic and cultural directions and reconsidering the “power imbalance” feature of cyberbullying.