DOI: 10.7910/dvn/ymzc30
title: Replication Data for: On the Mechanics of NFT Valuation: AI Ethics and Social Media

description: As CryptoPunks pioneers the innovation of non-fungible tokens (NFTs) in AI and art, the valuation mechanics of NFTs has become a trending topic. Earlier research identifies the impact of ethics and society on the price prediction of CryptoPunks. Since the booming year of the NFT market in 2021, the discussion of CryptoPunks has propagated on social media. Still, existing literature hasn't considered the social sentiment factors after the historical turning point on NFT valuation. In this paper, we study how sentiments in social media, together with gender and skin tone, contribute to NFT valuations by an empirical analysis of social media, blockchain, and crypto exchange data. We evidence social sentiments as a significant contributor to the price prediction of CryptoPunks. Furthermore, we document structure changes in the valuation mechanics before and after 2021. Although people's attitudes towards Cryptopunks are primarily positive, our findings reflect imbalances in transaction activities and pricing based on gender and skin tone. Our result is consistent and robust, controlling for the rarity of an NFT based on the set of human-readable attributes, including gender and skin tone. Our research contributes to the interdisciplinary study at the intersection of AI, Ethics, and Society, focusing on the ecosystem of decentralized AI or blockchain. We provide our data and code for replicability as open access on GitHub.
description: Meta Description of the data files

This dataset comprises several CSV files generated and processed during our research titled “On the Mechanics of NFT Valuation: AI Ethics and Social Media.”

queried_tweets_cryptopunk_2017_2022.csv: This file contains tweets related to CryptoPunks, specifically those with the hashtag #cryptopunk. The data was obtained using the Snscrape API.

tweets_cryptopunk_gender_skintone.csv: This file includes tweets related to gender and skin tone in CryptoPunks. It encompasses tweets with hashtags #cryptopunk and any of #female, #male, #dark, #light, #medium, #albino, #alien, #ape, #zombie. The data was obtained using the Snscrape API.

analyzed_tweet_volume_cryptopunk_2017_2022.csv: This file presents the daily tweet volume analysis for CryptoPunks from 2017 to 2022.

analyzed_sentiment_cryptopunk_2017_2022.csv: This file contains the daily sentiment scores for all CryptoPunks-related tweets, which were computed as part of our research.

analyzed_keyword_sentiment_and_frequency.csv: This file contains the daily sentiment scores for tweets related to gender and skin tone in CryptoPunks. Additionally, it includes frequency information for the corresponding keywords.

analyzed_gender_skintone_transaction_data.csv: This file includes data on the ratio of gender and skin color in CryptoPunks' transactions.

cryptopunks_gender_skintone_info.csv: This file comprises transaction data specifically related to CryptoPunks. We obtained this data using the Dune Analytics API.

Ethereum_Gas_Price_Daily_Average.csv: This file presents the daily average gas prices for Ethereum transactions, obtained from Etherscan.

ETH_USD.csv: This file contains the ETH/USD exchange rate data collected from investing.com.

merged_dataset_without_sentiment.csv: This file combines all the necessary data required for regression analysis, excluding sentiment scores.

merged_dataset_with_sentiment.csv: This file includes all the necessary data required for regression analysis, including sentiment scores.

Resources
Dune Analytics. n.d. “Dashboards.” Dune.com. https://dune.com/browse/dashboards.
etherscan.io. 2019. “Ethereum (ETH) Blockchain Explorer.” Ethereum (ETH) Blockchain Explorer. 2019. https://etherscan.io/.
Investing.com. 2023. “Investing.com - Stock Market Quotes & Financial News.” Investing.com. 2023. https://www.investing.com/.
JustAnotherArchivist. 2020. “JustAnotherArchivist/Snscrape.” GitHub. December 22, 2020. https://github.com/JustAnotherArchivist/snscrape.