This paper presents the first empirical analysis of how diverse token-based reward mechanisms impact platform dynamics and user behaviors. For this, we gather a unique, large-scale dataset from Farcaster. This blockchain-based, decentralized social network incorporates multiple incentive mechanisms spanning platform-native rewards, third-party token programs, and peer-to-peer tipping. Our dataset captures token transactions and social interactions from 574,829 wallet-linked users, representing 64.25% of the platform's user base. Our socioeconomic analyses reveal how different tokenomics design shape varying participation rates (7.6%--70%) and wealth concentration patterns (Gini 0.72--0.94), whereas inter-community tipping is 1.3--2x more frequent among non-following pairs, thereby mitigating echo chambers. Our causal analyses further uncover several critical trade-offs: (1) while most token rewards boost content creation, they often fail to enhance -- sometimes undermining -- content quality; (2) token rewards increase follower acquisition but show neutral or negative effects on outbound following, suggesting potential asymmetric network growth; (3) repeated algorithmic rewards demonstrate strong cumulative effects that may encourage strategic optimization. Our findings advance understanding of cryptocurrency integration in social platforms and highlight challenges in aligning economic incentives with authentic social value.