Having a substantial number of loyal users is a key for the success of online social platforms. When building a social platform where which users enjoy over a long period, it is crucial to identify predictive signals for long-term engagement, also known as user longevity. This dissertation analyzes and identifies key factors driving user longevity from three data-driven case studies.First, in an online multiplayer game where rich user behaviors are digitally logged, I investigated how factors driving longevity vary as user level increases. While achievement was the main factor in the lower-level stages, social features became the most important in predicting long-term engagement even after reaching the highest level. The varying key indicators across different levels suggest that it is necessary to consider virtual life phases to analyze user longevity indicators precisely. Second, I analyzed shared logs of MyFitnessPal on Twitter via the social sharing mechanism, and investigated whether additional information from another platform can be predictive of user longevity in the target platform. Cross-platform analysis demonstrates that features extracted from Twitter are predictive of long-term engagement in MyFitnessPal. This study shows that utilizing a supplementary social network via social sharing mechanism enables us to investigate potential factors driving longevity more diversely. Third, from a case study on the Reddit science community, I analyze the effects of disclosing offline social status on continued usages over an extended period. The design mechanism that reveals offline social status has been adopted to complement online reputation systems; however, it is not fully investigated how the design affects future engagement in online social platforms yet. From causal inferences on user longevity in Reddit science community, I found that disclosing academic degrees has a positive effect on continued usage over an extended period in the community. On the other hand, the design mechanism decreased social interactions toward those who do not reveal their offline status. The results suggest that the design mechanism should be carefully introduced to online social platforms because disclosed offline social status can create mixed effects on future engagements in online social platforms.To summarize, this dissertation conducts three data-driven case studies on identifying key factors driving user longevity in online social platforms, and presents a common finding on the importance of social factors across the three studies. Although each finding is from a specific case and hence cannot be generalized, future cross-platform studies could lead to building a social platform that users enjoy over an extended period.