DOI: 10.7910/dvn/zspbp7
title: Replication Data for: "Trust Dynamics and Market Behavior in Cryptocurrency: A Comparative Study of Centralized and Decentralized Exchanges"

description: In the evolving landscape of digital finance, the transition from centralized to decentralized trust mechanisms, primarily driven by blockchain technology, plays a critical role in shaping the cryptocurrency ecosystem. This paradigm shift raises questions about the traditional reliance on centralized trust and introduces a novel, decentralized trust framework built upon distributed networks. Our research delves into the consequences of this shift, particularly focusing on how incidents influence trust within cryptocurrency markets, thereby affecting trade behaviors in centralized (CEXs) and decentralized exchanges (DEXs). We conduct a comprehensive analysis of various events, assessing their effects on market dynamics, including token valuation and trading volumes in both CEXs and DEXs. Our findings highlight the pivotal role of trust in directing user preferences and the fluidity of trust transfer between centralized and decentralized platforms. Despite certain anomalies, the results largely align with our initial hypotheses, revealing the intricate nature of user trust in cryptocurrency markets. This study contributes significantly to interdisciplinary research, bridging distributed systems, behavioral finance, and Decentralized Finance (DeFi). It offers valuable insights for the distributed computing community, particularly in understanding and applying distributed trust mechanisms in digital economies, paving the way for future research that could further explore the socio-economic dimensions and leverage blockchain data in this dynamic domain.
description: Harvard Dataverse Description
• Overview Section
The data files originate from meticulous collection and analysis of Ethereum transaction data, with a particular focus on transactions involving Wrapped Ether (WETH). These datasets were meticulously compiled through SQL queries executed on Flipsidecrypto (https://flipsidecrypto.xyz/), a renowned platform offering comprehensive blockchain data insights. Spanning from January 1, 2021, to July 1, 2023, the datasets encompass crucial information on daily WETH prices denominated in USD, transaction volumes, net flows between centralized exchanges (CEX) and decentralized exchanges (DEX), as well as user traffic between these exchange platforms.
Comprising two primary datasets, this repository offers a holistic view of WETH transactions and user dynamics within the Ethereum ecosystem during the specified timeframe:
1. Daily Average Prices of WETH: This dataset correlates daily WETH prices with their respective dates, facilitating a nuanced understanding of price fluctuations over time. (File name: WETH_daily_average_price.csv.)
2. Transaction Volumes, Net Flows, and User Traffic Data: This dataset presents transaction volumes, net flows, and user traffic metrics between CEX and DEX, all denominated in USD and organized chronologically.
(File name: CEX_to_DEX_transaction.csv, DEX_to_CEX_transaction.csv, Netflow_transaction.csv.)

• Usage Notes
Utilizing the provided data files necessitates proficiency in handling structured data formats like Comma Separated Values (CSV). Moreover, employing data analysis and visualization tools such as Python with libraries like Pandas and Matplotlib can greatly aid in extracting meaningful insights from the datasets.
To effectively analyze the data, users are encouraged to follow these steps:
1. Data Loading: Import the CSV files into a suitable data analysis environment to begin exploration.
2. Data Preprocessing: Perform necessary preprocessing steps, such as addressing missing values or formatting data types, to ensure data integrity.
3. Data Visualization: Utilize visualization techniques to represent data graphically, enabling clearer interpretation of patterns and anomalies.
4. Statistical Analysis: Employ statistical methods to derive insights from the data, considering factors like daily average prices, transaction volumes, and net flows.