# TweetBoost: Influence of Social Media on NFT Valuation

arXiv: https://arxiv.org/abs/2201.08373 · HTML: https://mlsanity.com/paper/2201.08373/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jan 2022.

## Built on by (most cited first, 11 of 11)

- [Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning](https://mlsanity.com/paper/2306.11731/) (2023)
- [Show me your NFT and I tell you how it will perform: Multimodal representation learning for NFT selling price prediction](https://mlsanity.com/paper/2302.01676/) (2023)
- [EX-Graph: A Pioneering Dataset Bridging Ethereum and X](https://mlsanity.com/paper/2310.01015/) (2023)
- [NFT Appraisal Prediction: Utilizing Search Trends, Public Market Data, Linear Regression and Recurrent Neural Networks](https://mlsanity.com/paper/2204.12932/) (2022)
- [NFTVis: Visual Analysis of NFT Performance](https://mlsanity.com/paper/2306.02712/) (2023)
- [Exploring the Decentraland Economy: Multifaceted Parcel Attributes, Key Insights, and Benchmarking](https://mlsanity.com/paper/2404.07533/) (2024)
- [Digital Asset Valuation: A Study on Domain Names, Email Addresses, and NFTs](https://mlsanity.com/paper/2210.10637/) (2022)
- [Projecting Non-Fungible Token (NFT) Collections: A Contextual Generative Approach](https://mlsanity.com/paper/2210.15493/) (2022)
- [Visually Wired NFTs: Exploring the Role of Inspiration in Non-Fungible Tokens](https://mlsanity.com/paper/2303.17031/) (2023)
- [What Determines the Price of NFTs?](https://mlsanity.com/paper/2310.01815/) (2023)
- [SocialFiVis: A Visual Analytics Sandbox for LLM-Grounded Multi-Agent Simulation in Social Finance](https://mlsanity.com/paper/2608.08497/) (2026)

## Abstract (arXiv)

NFT or Non-Fungible Token is a token that certifies a digital asset to be unique. A wide range of assets including, digital art, music, tweets, memes, are being sold as NFTs. NFT-related content has been widely shared on social media sites such as Twitter. We aim to understand the dominant factors that influence NFT asset valuation. Towards this objective, we create a first-of-its-kind dataset linking Twitter and OpenSea (the largest NFT marketplace) to capture social media profiles and linked NFT assets. Our dataset contains 245,159 tweets posted by 17,155 unique users, directly linking 62,997 NFT assets on OpenSea worth 19 Million USD. We have made the dataset public. We analyze the growth of NFTs, characterize the Twitter users promoting NFT assets, and gauge the impact of Twitter features on the virality of an NFT. Further, we investigate the effectiveness of different social media and NFT platform features by experimenting with multiple machine learning and deep learning models to predict an asset's value. Our results show that social media features improve the accuracy by 6% over baseline models that use only NFT platform features. Among social media features, count of user membership lists, number of likes and retweets are important features.