Web3 projects have effectively used token airdrops to distribute tokens to users, aiming to drive adoption, decentralization, and network effects. These airdrops align incentives and reward participation, but they are vulnerable to Sybil attacks, where users create multiple wallets to claim disproportionate amounts of tokens, jeopardizing fairness and economic stability. This paper explores analytical and non-analytical methods to mitigate Sybil attacks in airdrop design. Analytical methods, such as network analysis using the Louvain method and clustering analysis using OPTICS, leverage transaction data to identify suspicious patterns. Our integrated analytics approach combines network and clustering techniques for improved detection accuracy, offering insights for designing fair and resilient airdrop campaigns. Case studies of projects like LayerZero, Uniswap, Optimism, and Jupiter illustrate practical implementations and outcomes. This study emphasizes the importance of balancing Sybil resistance with user experience and project goals for sustainable token distribution.