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How Social Engagement Drove NFT Market Success in 2022by@cryptopunk
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How Social Engagement Drove NFT Market Success in 2022

by Ruslan GromovMarch 21st, 2025
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NFT success depends on social engagement, with Twitter playing a major role. BAYC’s community influence surpasses CryptoPunks, proving that liquidity and value stem from active social interactions.

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Authors:

(1) SIMONE CASALE-BRUNET, École Polytechnique Fédérale de Lausanne, Switzerland;

(2) MIRKO ZICHICHI, Universidad Politécnica de Madrid, Spain;

(3) LEE HUTCHINSON, WhaleAnalytica.com, Switzerland;

(4) MARCO MATTAVELLI, École Polytechnique Fédérale de Lausanne, Switzerland;

(5) STEFANO FERRETTI, University of Urbino “Carlo Bo”, Italy.

1 Introduction

2 State of Art

3 Projects Selection and Data Collection

3.1 Blockchain data

3.2 Twitter data

4 Data Analysis and Results

4.1 Ethereum wallets and Twitter users and 4.2 The communities

4.3 Hashtags

4.4 The role of the social network community

5 Conclusions and References

5 CONCLUSIONS

The NFT phenomenon is a topic that became mainstream during 2021 and has continued to receive increasing attention from early 2022 to the present. This blockchain-based technology has also come to the forefront thanks to projects such as BAYCs whose images have been purchased by celebrities and traded at very high prices as reported by several media. In this paper, we analyzed the phenomenon of NFTs, focusing on the class related to PFPs. We chose 18 projects based on our knowledge in the field and based on their importance in terms of volumes traded, users, and social activity. It was illustrated through analysis of social activity how the concept of social community is essential to ensure liquidity and value of PFP projects, i.e., used as social icons. The centrality and influence of the community related to BAYCs was demonstrated, that despite being second to CryptoPunks in terms of volumes traded, social activity is much higher and central to every other project in the industry. This work aimed to lay the groundwork for more in-depth future studies on understanding whether patterns and causality conditions may exist between elements such as the number of tweets, average price of a collection, Twitter users, and Ethereum wallet.

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This paper is available on arxiv under CC BY 4.0 DEED license.