Market Responses to Genuine Versus Strategic Generosity: An Empirical Examination of NFT Charity Fundraisers

• URL: http://arxiv.org/abs/2401.12064v1
• Date: Mon, 22 Jan 2024 15:58:47 GMT
• Title: Market Responses to Genuine Versus Strategic Generosity: An Empirical Examination of NFT Charity Fundraisers
• Authors: Chen Liang, Murat Tunc, Gordon Burtch
• Abstract summary: Nonfungible token (NFT) charity fundraisers involve the sale of NFTs of artistic works with the proceeds donated to philanthropic causes. We investigate the causal effect of purchasing an NFT within the charity fundraiser on a donor's later market outcomes. We show that charity-NFT "relisters" experience significant penalties in the market, in terms of the prices they are able to command on other NFT listings.
• Score: 15.310650714527602
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Crypto donations now represent a significant fraction of charitable giving worldwide. Nonfungible token (NFT) charity fundraisers, which involve the sale of NFTs of artistic works with the proceeds donated to philanthropic causes, have emerged as a novel development in this space. A unique aspect of NFT charity fundraisers is the significant potential for donors to reap financial gains from the rising value of purchased NFTs. Questions may arise about the motivations of donors in these charity fundraisers, resulting in a negative social image. NFT charity fundraisers thus offer a unique opportunity to understand the economic consequences of a donor's social image. We investigate these effects in the context of a large NFT charity fundraiser. We identify the causal effect of purchasing an NFT within the charity fundraiser on a donor's later market outcomes by leveraging random variation in transaction processing times on the blockchain. Further, we demonstrate a clear pattern of heterogeneity, based on an individual's decision to relist (versus hold) the purchased charity NFTs (a sign of strategic generosity), and based on an individual's degree of social exposure within the NFT marketplace. We show that charity-NFT "relisters" experience significant penalties in the market, in terms of the prices they are able to command on other NFT listings, particularly among those who relist quickly and those who are more socially exposed. Our study underscores the growing importance of digital visibility and traceability, features that characterize crypto-philanthropy, and online philanthropy more broadly.

Related papers

• A Latent Dirichlet Allocation (LDA) Semantic Text Analytics Approach to Explore Topical Features in Charity Crowdfunding Campaigns [0.6298586521165193]
  This study introduces an inventive text analytics framework, utilizing Latent Dirichlet Allocation (LDA) to extract latent themes from textual descriptions of charity campaigns. The study has explored four different themes, two each in campaign and incentive descriptions. The study was successful in using Random Forest to predict success of the campaign using both thematic and numerical parameters.
  arXiv  Detail & Related papers  (2024-01-03T09:17:46Z)
• How NFT Collectors Experience Online NFT Communities: A Case Study of Bored Ape [0.0]
  Non-fungible tokens (NFTs) are unique cryptographic assets representing the ownership of digital media. This study explores the experiences of NFT collectors within the online NFT community.
  arXiv  Detail & Related papers  (2023-09-17T16:48:37Z)
• Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning [69.60868581184366]
  We propose a Diffusion-based generation framework with Multiple Visual-Policies as rewards for NFT images. The proposed framework consists of a large language model (LLM), a diffusion-based image generator, and a series of visual rewards by design. Our framework can generate NFT images showing more visually engaging elements and higher market value, compared with SOTA approaches.
  arXiv  Detail & Related papers  (2023-06-20T17:59:46Z)
• Unveiling the Risks of NFT Promotion Scams [24.54041279375181]
  We study 439 promotion services (accounts) on Twitter that have collectively promoted 823 unique NFT projects. More than 36% of these projects were fraudulent, comprising of phishing, rug pull, and pre-mint scams. We develop a machine learning tool that was able to proactively detect 382 new fraudulent NFT projects on Twitter.
  arXiv  Detail & Related papers  (2023-01-24T04:13:44Z)
• A Game of NFTs: Characterizing NFT Wash Trading in the Ethereum Blockchain [53.8917088220974]
  The Non-Fungible Token (NFT) market experienced explosive growth in 2021, with a monthly trade volume reaching $6 billion in January 2022. Concerns have emerged about possible wash trading, a form of market manipulation in which one party repeatedly trades an NFT to inflate its volume artificially. We find that wash trading affects 5.66% of all NFT collections, with a total artificial volume of $3,406,110,774.
  arXiv  Detail & Related papers  (2022-12-02T15:03:35Z)
• Probably Something: A Multi-Layer Taxonomy of Non-Fungible Tokens [62.997667081978825]
  Non-Fungible Tokens (NFTs) are hyped and increasingly marketed as essential building blocks of the Metaverse. This paper aims to establish a fundamental and comprehensive understanding of NFTs by identifying and structuring common characteristics within a taxonomy.
  arXiv  Detail & Related papers  (2022-08-29T18:00:30Z)
• A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability [59.80140875337769]
  Graph Neural Networks (GNNs) have made rapid developments in the recent years. GNNs can leak private information, are vulnerable to adversarial attacks, can inherit and magnify societal bias from training data. This paper gives a comprehensive survey of GNNs in the computational aspects of privacy, robustness, fairness, and explainability.
  arXiv  Detail & Related papers  (2022-04-18T21:41:07Z)
• "It's A Blessing and A Curse": Unpacking Creators' Practices with Non-Fungible Tokens (NFTs) and Their Communities [9.270221748331096]
  We focus on NFT creators and present results of an exploratory qualitative study. Our participants had nuanced feelings about NFTs and their communities. We discuss how the built-in properties of blockchains and NFTs might have contributed to some of these issues.
  arXiv  Detail & Related papers  (2022-01-15T08:52:26Z)
• Under the Skin of Foundation NFT Auctions [0.0]
  We studied one of the most prominent marketplaces dedicated to NFT auctions and trades, Foundation. We performed social network analysis on a graph that we had created based on transferred NFTs on Foundation. We built a neural network-based similarity model for retrieving and clustering similar NFTs.
  arXiv  Detail & Related papers  (2021-09-25T09:01:44Z)
• How COVID-19 Have Changed Crowdfunding: Evidence From GoFundMe [77.34726150561087]
  This study uses a unique data set of all the campaigns published over the past two years on GoFundMe. We study a corpus of crowdfunded projects, analyzing cover images and other variables commonly present on crowdfunding sites.
  arXiv  Detail & Related papers  (2021-06-18T08:03:58Z)
• Batch Normalization Increases Adversarial Vulnerability and Decreases Adversarial Transferability: A Non-Robust Feature Perspective [91.5105021619887]
  Batch normalization (BN) has been widely used in modern deep neural networks (DNNs) BN is observed to increase the model accuracy while at the cost of adversarial robustness. It remains unclear whether BN mainly favors learning robust features (RFs) or non-robust features (NRFs)
  arXiv  Detail & Related papers  (2020-10-07T10:24:33Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.