Bridging Culture and Finance: A Multimodal Analysis of Memecoins in the Web3 Ecosystem
Hou-Wan Long, Nga-Man Wong, Wei Cai
TL;DR
Memecoins fuse internet culture with decentralized finance, but prior work largely treated culture and finance separately. We introduce the Coin-Meme dataset, an open multimodal resource combining textual, visual, community, and financial data for 3,751 Solana memecoins, and a framework that jointly analyzes cultural narratives and market dynamics using LDA topic modeling, ResNet50 visual embeddings, and key financial metrics. By applying clustering, sentiment analysis, and word-cloud visualization, we identify three thematic groups—humor, animals, and political satire—and reveal how cultural signals relate to Market Entry Time and Market Capitalization. This work provides a resource and methodology for studying memecoin adoption in Web3, with implications for understanding governance, community behavior, and risk in culturally driven financial ecosystems.
Abstract
Memecoins, driven by social media engagement and cultural narratives, have rapidly grown within the Web3 ecosystem. Unlike traditional cryptocurrencies, they are shaped by humor, memes, and community sentiment. This paper introduces the Coin-Meme dataset, an open-source collection of visual, textual, community, and financial data from the Pump.fun platform on the Solana blockchain. We also propose a multimodal framework to analyze memecoins, uncovering patterns in cultural themes, community interaction, and financial behavior. Through clustering, sentiment analysis, and word cloud visualizations, we identify distinct thematic groups centered on humor, animals, and political satire. Additionally, we provide financial insights by analyzing metrics such as Market Entry Time and Market Capitalization, offering a comprehensive view of memecoins as both cultural artifacts and financial instruments within Web3. The Coin-Meme dataset is publicly available at https://github.com/hwlongCUHK/Coin-Meme.git.