Purpose: Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors. Design/methodology/approach: We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis. Findings: The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution. Originality/value: Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

Based on motivational theory, this study investigated the effect of users’ knowledge seeking on users’ knowledge contribution in question-and-answer (Q&A) communities. We collected 4643 samples from the largest social Q&A platform in China (Zhihu) and applied a mediation effect test to the data. The results showed that knowledge seeking affects intrinsic motivations (altruism and self-efficacy) and extrinsic motivations (social support, group identity, and reputation), further affecting knowledge contribution. Our findings indicated that Q&A communities should be concerned with users’ intrinsic and extrinsic motivations to ensure balanced knowledge exchange on social Q&A platforms, ultimately fostering long-term stability and growth. Existing research has mainly focused on a single behavioral state, such as knowledge seeking or knowledge contribution, and has paid little attention to the connection between these two types of user information behaviors. This study aimed to fill this gap by revealing the mechanisms through which users’ knowledge seeking affects their knowledge contribution.

This study investigates the mechanisms driving users' transitions from knowledge seeking to knowledge contribution behaviors in social question-and-answer communities, with the goal of advancing theoretical understanding and promoting the sustainable development of these platforms. Grounded in motivation theory and trust theory, this study develops and tests a research model using covariance-based structural equation modeling and bootstrap method with 452 valid samples. The results reveal that knowledge seeking behavior positively influences both intrinsic motivations (altruism, self-efficacy, emotional empathy) and extrinsic motivations (platform reward, social need, group identity), with all motivations except emotional empathy significantly promoting knowledge contribution behavior. Furthermore, intrinsic (altruism, self-efficacy) and extrinsic motivations (platform reward, social need, group identity) partially mediate the relationship between knowledge seeking and contribution behaviors. Moderation analysis indicates that platform trust and interpersonal trust strengthen this relationship, with interpersonal trust having a stronger effect. Notably, moderation analysis indicates that platform trust and interpersonal trust strengthen this relationship, with interpersonal trust exhibiting a stronger effect. By integrating motivation theory and trust theory, this study provides a unified framework to examine the transition from knowledge seeking to contribution behaviors from theoretical, behavioral, and contextual perspectives. The findings offer practical implications for social question-and-answer community managers, including strategies to diversify reward systems, enhance users' self-efficacy and group identity, foster meaningful social interactions, and establish multi-level trust mechanisms to promote long-term platform engagement and growth.