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This study aims to explore the impact of engaging in serious leisure (SL) on the well-being (WB) and self-perceived employability (PE) of university students while also considering the role of career adaptability (CA) as a mediator.

A total of 905 domestic undergraduate students from China completed an online survey.

The findings reveal that participation in SL positively influences WB and PE. Additionally, the results indicate that CA mediates the SL-WB relationship but not the SL-PE relationship.

The theoretical contribution of this research comes from advancing our understanding of sustainable career theory through empirical testing of SL, PE, and CA on WB outcomes within a higher education setting. The practical implications of this study involve providing universities with strategies to support domestic Chinese undergraduate students in enhancing their WB and PE through active engagement in SL pursuits and the development of CA. Moreover, our findings serve as a foundation for future research investigating whether insights gained from domestic Chinese undergraduate students can provide solutions on a global scale to address the persistent challenges of improving student WB and PE.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

The COVID-19 pandemic necessitated teleworking, which inadvertently led to an impaired communication between supervisors and employees, resulting in abusive supervision. Drawing on the conservation of resources (COR) theory and the social identity theory, this study aims to address this negative association by examining the mediating role of state mindfulness and the moderating role of COVID-19 corporate social responsibility (CSR) in the relationship between abusive supervision and counterproductive work behaviors.

This research employs both qualitative and quantitative research designs. Data collection involved an experimental design with 117 participants (Study 1), a cross-sectional survey with 243 participants (Study 2) and semi-structured interviews with 24 full-time employees (Study 3).

The results reveal that state mindfulness acts as a mediator in the positive relationship between abusive supervision and counterproductive work behaviors (CWB). Furthermore, COVID-19 CSR mitigates the relationship between abusive supervision and CWB within the organization, but not with the supervisor. Additionally, COVID-19 CSR moderates the impact of abusive supervision on state mindfulness.

The results emphasize the crucial role of CSR when employees encounter abusive supervision during the COVID-19 pandemic. Organizations and managers should adopt appropriate strategies to enhance employees' perception of CSR. Prioritizing the cultivation of state mindfulness is also recommended, and organizations can provide short-term mindfulness training to improve employees' state mindfulness.

This research contributes to the understanding of abusive supervision and CWB in the context of forced teleworking.