HNDS-R: Understanding Drivers of Trust in Cryptocurrency Using Big Data and Ethnographic Approaches

加密货币市场在全球经济市场中所占份额越来越大，但波动性要大得多。这种波动性在一定程度上是由加密货币用户对加密货币市场的信任决定的。因此，加密货币市场的危机为理解信任、市场和监管行动之间的关系提供了关键窗口。该项目利用加密货币市场的危机和复苏，调查对根据市场动态调整信任的水平和基本理由的影响。项目调查人员关注利益相关者之间的重要差异，并向政策制定者、监管机构、行业专业人员和科学家广泛传播研究结果。该项目还为本科生和研究生提供数据收集和分析的科学方法方面的培训，并包括科学研究中代表性不足的学生和学者。该项目测试了几个非互斥假说，这些假说表明：一)当加密货币市场的扰动被视为严重而不是长期时，二)当投资被视为更多而不是博弈时，三)当参与社区促进信任时；以及四)由于加密货币市场系统的基本信念的差异。人类学家和研究人员在技术管理和计算机科学方面的独特合作被用来综合理论和方法，以激励对大规模数据的尖端分析，捕捉信任和声明的加密货币市场参与之间的广泛和深入的关系。具体地说，调查人员将大数据方法与民族志方法结合起来，前者使用自然语言处理分析围绕灾难性市场低迷的社交媒体数据，后者包括网络图、参与者观察、调查和采访。这样的纵向分析为市场系统的信任随着时间的推移以及与个人特征和更广泛的监管场景的关系提供了独特的见解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The cryptocurrency market represents an increasing share of global economic markets, yet is considerably more volatile. This volatility is shaped in part by the trust that cryptocurrency users place in the cryptocurrency market. Accordingly, crises in cryptocurrency markets offer critical windows for understanding relationships between trust, markets, and regulatory actions. This project leverages crises and recoveries in cryptocurrency markets to investigate impacts on the levels of and underlying rationales for adjusting trust based on market dynamics. Project investigators attend to important variation across stakeholders and disseminate research findings broadly to policymakers, regulators, industry professionals, and scientists. The project also provides training for undergraduate and graduate students in scientific methods of data collection and analysis and includes underrepresented students and scholars in scientific research.The project tests several non-mutually exclusive hypotheses that suggest that trust can be maintained i) when perturbations in cryptocurrency markets are seen as acute versus long-term, ii) when investments are seen as more versus less game-like, iii) when participation in communities facilitate trust; and iv) due to variation in underlying beliefs in cryptocurrency market systems. A unique collaboration between anthropologists and researchers in technology management and computer science is leveraged to synthesize theory and method to motivate cutting-edge analyses of large-scale data capturing broad and deep relationships between trust and stated cryptocurrency market involvement. Specifically, the investigators combine big data methods, using natural language processing analysis of social media data surrounding catastrophic market downturns, with ethnographic methods, including netnography, participant observation, surveys and interviews. Such longitudinal analyses provide unique insights into the ways trust in market systems shift over time and in relation to individual characteristics and broader regulatory scenarios.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.