The Characterisation of Intergenerational Social Support Needs Based on the Virtual Community Douban Group

Abstract

This study focuses on the Cross-Age Group Troubles Exchange group on Douban, a popular Chinese social media platform, as its primary research subject. Through systematic analysis of 1,446 user-generated posts within this digital forum, the study examines the discursive patterns through which multi-generational users articulate anxieties and negotiate mutual support. Employing computational methodologies including Latent Dirichlet Allocation (LDA) topic modeling and lexicon-based sentiment analysis, three dominant thematic clusters are identified: marital relationships, familial obligations, and career progression trajectories, each demonstrating significant age-cohort correlations. These dialogues reveal both transgenerational emotional resonance and statistically verifiable intergenerational divergences. Affective analysis further indicates that 83.6% (n=1,209) of posts manifest constructive help-seeking behaviors, thereby empirically substantiating virtual communities' efficacy as social support infrastructures. The research elucidates t he operational mechanisms whereby cross-age digital collectives’ mediate anxiety through digitally facilitated peer interactions, advancing novel theoretical propositions regarding the evolutionary dynamics of online social support ecosystems.