Abstract:

[Purpose/Significance] With the expansion of user-generated content (UGC) communities, users have increasingly engaged in interaction behaviors that go beyond passive consumption. Among these behaviors, urging creators to update content has emerged as a distinctive form of user participation. Unlike conventional feedback behaviors that respond to existing content, urging behavior is future-oriented and directly intervenes in the content production process, reflecting users' expectations, motivations, and relational orientations toward creators. Despite its growing visibility, research in the field of library and information science (LIS) rarely examines urging behavior as an independent object of analysis. Theoretical investigation of its behavioral logic and formation mechanisms remains deficient. This study aims to systematically explore how urging behavior emerges and evolves, and how it is shaped by multiple influencing factors. This will contribute to a deeper understanding of how users interact with information in UGC communities. [Method/Process] This study adopts the grounded theory approach, conducting in-depth interviews with 20 active users in the UGC communities. Data were collected and analyzed using Nvivo11 software through a three-level coding process, including open coding, axial coding, and selective coding. [Results/Conclusions] The study constructs two interrelated analytical models. First, a dynamic behavioral pathway model is developed, revealing urging behavior as a cyclical process. The process is initially triggered by either cognitive motivations or emotional motivations. These motivations drive users to engage in three distinct types of urging behavior: semantic expression-based urging, quick operation-based urging, and economic incentive-based urging. Users then receive positive or negative feedback from creators or the community, which leads them to conduct subjective evaluations of their urging experience in terms of emotional responses and perceived effectiveness. These evaluations subsequently influence users' future motivations, forming a continuous feedback loop. Second, a comprehensive influencing-factor model is established, identifying five categories of core factors: user characteristics, content attributes, creator attributes, platform characteristics, and situational factors. The study further clarifies the complex interactions among these factors. User-related factors and content-related factors exert direct effects on urging behavior. Content factors and creator factors also generate indirect effects through the mediating role of user factors. In contrast, platform characteristics and situational factors function as moderating variables that shape the strength of the relationship between user factors and urging behavior. Together, these findings provide a nuanced explanation of why and how users engage in urging behavior. The study discusses the theoretical contributions of integrating the behavioral pathway model with the influencing-factor model and offers preliminary practical implications for platform governance and creator strategies. Limitations include the qualitative nature of the study and the relatively small sample size. Future research is encouraged to conduct quantitative validation and cross-platform comparative analyses to further extend these findings.

Key words: UGC community, content update prompting behavior, grounded theory, behavioral pathways, AI dependence, internet addiction, information behavior