The article explores the intersection of blockchain and social media through an analysis of Ethereum transactions and Twitter interactions. Using Google BigQuery, researchers structured blockchain data, focusing primarily on NFT trades and associated user behaviors. By excluding gas fees and concentrating on ETH transactions, the study aims to unveil trading volumes and community dynamics within the Ethereum ecosystem. Additionally, Twitter data is analyzed to assess its role in influencing NFT markets and fostering community development.
The analysis leverages blockchain data structured via Google BigQuery for efficient transactions and relationships in Ethereum, allowing comprehensive evaluation of NFT markets.
By excluding gas fees and focusing on ETH-related transactions, we ensure a clearer view of the trading and behavioral patterns within Ethereum communities.
The public nature of Ethereum blockchain ensures data accessibility, which is crucial for analyzing transaction patterns and community engagement in NFT trading.
Twitter data complements blockchain analysis, revealing how social media interactions influence NFT trading and the formation of communities around blockchain technology.
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