Blockchain Papers

Ding Bao, Wei Ren, Yuexin Xiang, Weimao Liu · 7 authors

No abstract is available for this record.

Lucio La Cava, Davide Costa, Andrea Tagarelli

The fervor for Non-Fungible Tokens (NFTs) attracted countless creators, leading to a Big Bang of digital assets driven by latent or explicit forms of inspiration, as in many creative processes. This work exploits Vision Transformers and graph-based modeling to delve into visual inspiration phenomena between NFTs over the years, i.e., the visual influence that can be detected whenever an NFT appears to be visually close to another that was published earlier in the market. Our goals include unveiling the main structural traits that shape visual inspiration networks, exploring the interrelation between visual inspiration and asset performances, investigating crypto influence on inspiration processes, and explaining the inspiration relationships among NFTs. Our findings unveil how the pervasiveness of inspiration led to a temporary saturation of the visual feature space, the impact of the dichotomy between inspiring and inspired NFTs on their financial performance, and an intrinsic self-regulatory mechanism between markets and inspiration waves. Our work can serve as a starting point for gaining a broader view of the evolution of Web3.

Yifan Cao, Xingxing Yang, Meng Xia, Hongkun Liu · 10 authors

Non-fungible tokens (NFTs) can certify the authenticity and scarcity of digital assets on the blockchain. There is an urgent need to identify impact attributes from various potential factors and further evaluate NFT collectibles. Nevertheless, the task is challenging due to the massive amount of heterogeneous and multi-modal data (e.g., social media text, numerical transaction data, and images) in NFT transactions. To this end, we present an interactive visual analytics system, NFTeller, that provides a dual-centric perspective analysis of NFT transactions. The system i) summarizes the temporal evolution and correlation of transaction patterns and dynamic impact attributes of NFT collection projects; ii) presents an augmented chord diagram with a radial stacked bar chart for exploring the co-collected projects and co-occurring whale accounts. We derive in-depth insights from case studies on a real data set to evaluate the systems’ effectiveness and usability.

Fangfang Zhou, Yunpeng Chen, Chunyao Zhu, Lijia Jiang · 9 authors

Blockchain-based cryptocurrencies, such as Bitcoin (BTC) and Ethereum (ETH), are newly emerging financial assets. Cryptocurrency exchanges are marketplaces for cryptocurrency circulation while becoming a new venue for money laundering. In this work, we cooperate with a cryptocurrency exchange to investigate new solutions for anti-money laundering in cryptocurrency exchanges. First, we learn the domain knowledge of cryptocurrency transactions and summarize data analytical requirements of transaction supervisors in their daily work of anti-money laundering. Then, we propose a visual analysis approach to support their daily work. The approach consists of a new algorithm that automatically detects suspicious money laundering accounts and a multiviewed user interface that visualizes the algorithm results and relevant transaction data. An abacus-inspired visualization is designed in the interface to depict transaction patterns contained in numerous cryptocurrency transactions, which can help supervisors find money laundering clues and deduce the trading tactic adopted by launderers. Finally, an algorithm performance experiment, a case study, and a field study are conducted with real-world data to demonstrate the effectiveness of our solution.

Kensuke Ito

Abstract This statement presents the author’s proposition—“Let’s be more conceptual!”—in response to the attempt to interpret Non-Fungible Tokens (NFTs) as contemporary art. In the context of NFTs, this opinion has the significance of finding artistry in the underlying decentralized autonomous consensus-building, and in the context of contemporary art, it has the significance of leading to the revival of early conceptual art. The second half of this statement covers the novelty and feasibility of this opinion, referring to precedents in art and engineering.

Yujing Sun, Hao Xiong, Siu Ming Yiu, Kwok‐Yan Lam

Bitcoin is gaining ever increasing popularity. However, professional skills are required if people want to check bitcoin transaction information from the blockchain. As pointed out in a recent study, there is a lack of tools to support effective interactive investigation of bitcoin transactions. Therefore, we present a novel visualization system,BitAnalysis, for interactive bitcoin wallet investigation. The analytical and visualization functions ofBitAnalysisare defined and developed by following the advice and requirements of a group of entrepreneurs and regulators of bitcoin-related business.BitAnalysisprovides a rich set of functions and intuitive visual interfaces for the users, such as law-enforcement officers and regulators, to effectively visualize and analyze the transactions of a bitcoin wallet (i.e., a cluster of bitcoin addresses) and its related wallets, to track the flow of bitcoins, and to identify wallet correlation using our novel clustering functions. To achieve these functions, we have designed new visualization techniques for presenting bitcoin transactions information and introduced theconnection diagramandbitcoin flow mapas new ways of analyzing, tracking and monitoring the trading activities of a cluster of closely related wallets. We also present an extensive user study that validated the effectiveness and usability ofBitAnalysis.

Natkamon Tovanich

Analyse visuelle pour la surveillance et l'exploration des données de la blockchain Bitcoin Bitcoin est une crypto-monnaie pionnière qui enregistre les transactions dans un registre public et distribué appelé blockchain. Il est utilisé comme support pour les paiements, les investissements et plus largement la gestion d’un portefeuille numérique qui n’est pas administré par un gouvernement ou une institution financière. Au cours de ces dix dernières années, l’activité transactionnelle de Bitcoin a rapidement et largement augmenté. La volumétrie ainsi que la nature évolutive de ces données posent des défis pour l’analyse et l'exploration des usages ainsi que des activités sur la blockchain. Le domaine de l’analyse visuelle travaille sur la conception de systèmes analytiques qui permettent aux humains d'interagir et d'obtenir des informations à partir de données complexes. Dans cette thèse, j'apporte plusieurs contributions à l'analyse des activités de minage sur la blockchain Bitcoin. Tout d'abord, je propose une caractérisation des travaux passés et des défis de recherche liés à l’analyse visuelle pour les blockchains. À partir de cette étude, j'ai proposé un outil d’analyse visuelle pour comprendre les activités de minage qui sont essentielles pour maintenir l'intégrité et la sécurité des données sur la blockchain Bitcoin. Je propose une méthode pour extraire l’activité des mineurs à partir des données de transaction et tracer leur comportement de bascule d’un pool de minage à un autre. L'analyse empirique de ces données a notamment révélé que les nouveaux pools de minage offraient une meilleure incitation et attiraient davantage de mineurs. Cette analyse a également montré que les mineurs choisissaient stratégiquement leur pool de minage dans le but de maximiser leur profit. Pour explorer l'évolution et la dynamique de cette activité sur le long terme, j'ai développé un outil d’analyse visuelle, appelé MiningVis, qui intègre des données liées au comportement des mineurs avec des informations contextuelles issues des statistiques et de l’actualité de Bitcoin. L'étude avec des utilisateurs démontre que les participants au minage de Bitcoin cherchent à utiliser l'outil pour analyser l'activité globale plutôt que pour étudier les détails d’un pool de minage. Les commentaires des participants prouvent que l'outil les a aidés à mettre en relation plusieurs informations et à découvrir les tendances dans l’activité de minage de Bitcoin.

Pietro Manganelli Conforti, matteo emanuele, Pietro Nardelli, Giuseppe Santucci · 5 authors

No abstract is available for this record.

James P Kerr, Max Rioux, Tomas Surna, Fabio Marcellus · 5 authors

NoteTogether [1] seeks to bring interactivity to a very crucial aspect of online learning: consuming video media. We developed a hybrid distributed platform that provides a shared space for watching and annotating video media. Analytics are provided to all users to highlight how users are interacting with a video. NoteTogether utilizes Ethereum Blockchain to ensure data security and scalability by offloading data storage and processing requirements to the distributed Ethereum network.

Natkamon Tovanich, Nicolas Soulié, Nicolas Heulot, Petra Isenberg

We present a visual analytics tool, MiningVis, to explore the long-term historical evolution and dynamics of the Bitcoin mining ecosystem. Bitcoin is a cryptocurrency that attracts much attention but remains difficult to understand. Particularly important to the success, stability, and security of Bitcoin is a component of the system called "mining." Miners are responsible for validating transactions and are incentivized to participate by the promise of a monetary reward. Mining pools have emerged as collectives of miners that ensure a more stable and predictable income. MiningVis aims to help analysts understand the evolution and dynamics of the Bitcoin mining ecosystem, including mining market statistics, multi-measure mining pool rankings, and pool hopping behavior. Each of these features can be compared to external data concerning pool characteristics and Bitcoin news. In order to assess the value of MiningVis, we conducted online interviews and insight-based user studies with Bitcoin miners. We describe research questions tackled and insights made by our participants and illustrate practical implications for visual analytics systems for Bitcoin mining.

Milán Janosov, Flóra Borsi

In this piece, we overview Isaac Asimov's most iconic work, the Foundation series, with two primary goals: to provide quantitative insights about the novels and bridge data science with digital art. First, we rely on data science and text processing tools to describe certain properties of Asimov's career and the novels, focusing on the different worlds in Asimov's universe. Then we transform the books' texts into a network centered around Asimov's planets and their semantic context. Finally, we introduce the world of crypto art and non-fungible tokens (NFTs) by transforming the visualized network into a high-end digital piece of art minted as an NFT. Additionally, to pay tribute to Asimov's devotion to robotics and artificial intelligence, we use OpenAI's Generative Pre-trained Transformer 3 (GPT-3) to draft several paragraphs of this paper.

Christoph Kinkeldey, Jean‐Daniel Fekete, Tanja Blascheck, Petra Isenberg

We present BitConduite, a visual analytics approach for explorative analysis of financial activity within the Bitcoin network, offering a view on transactions aggregated by entities, i.e., by individuals, companies, or other groups actively using Bitcoin. BitConduite makes Bitcoin data accessible to nontechnical experts through a guided workflow around entities analyzed according to several activity metrics. Analyses can be conducted at different scales, from large groups of entities down to single entities. BitConduite also enables analysts to cluster entities to identify groups of similar activities as well as to explore characteristics and temporal patterns of transactions. To assess the value of our approach, we collected feedback from domain experts.

Cüneyt Gürcan Akçora, Yulia R. Gel, Murat Kantarcıoğlu

Abstract Blockchain is an emerging technology that has enabled many applications, from cryptocurrencies to digital asset management and supply chains. Due to this surge of popularity, analyzing the data stored on blockchains poses a new critical challenge in data science. To assist data scientists in various analytic tasks for a blockchain, in this tutorial, we provide a systematic and comprehensive overview of the fundamental elements of blockchain network models. We discuss how we can abstract blockchain data as various types of networks and further use such associated network abstractions to reap important insights on blockchains' structure, organization, and functionality. This article is categorized under: Technologies > Data Preprocessing Application Areas > Business and Industry Fundamental Concepts of Data and Knowledge > Data Concepts Fundamental Concepts of Data and Knowledge > Knowledge Representation

Cüneyt Gürcan Akçora, Murat Kantarcıoğlu, Yulia R. Gel

Blockchain is an emerging technology that has enabled many applications, from\ncryptocurrencies to digital asset management and supply chains. Due to this\nsurge of popularity, analyzing the data stored on blockchains poses a new\ncritical challenge in data science.\n To assist data scientists in various analytic tasks on a blockchain, in this\ntutorial, we provide a systematic and comprehensive overview of the fundamental\nelements of blockchain network models. We discuss how we can abstract\nblockchain data as various types of networks and further use such associated\nnetwork abstractions to reap important insights on blockchains' structure,\norganization, and functionality.\n

Aleš Berger, Milan Košťák, Bruno Ježek

No abstract is available for this record.

Srinidhi Srinivasan, Rubasri Sundar, Sam Joy Herald Immanuel, Ramesh Belvadi · 5 authors

The emergence of cryptocurrency has sparked an interesting debate on the future of financial transactions. Post-COVID, there will be unbelievable advancements in the most popular and promising technology, cryptocurrency particularly bitcoins, as it is more valuable than any form of cryptocurrencies. Our work is about bitcoin price alert system using bolt Internet of Things (IOT) and Blockchain. In this research paper, we will be writing a python program that checks the current price of the bitcoin and sends an alert if the current price of the bitcoin is higher than the set selling price. The program checks the current price of bitcoins whenever the price of bitcoins is updated. And at that same time it compares the current price with the bitcoin price that has been set as selling price. It alerts through buzzer, email and message. For this we use Bolt Internet of Things (IOT) module and ubuntu software for writing program in python.

Li Zhen, Jinze Li, Yi Zheng, Baiqiang Dong

Blockchain is a public distributed ledger, which has the characteristics of decentralization and anonymization, which leads to the frequent occurrence of money laundering and theft. Taking Bitcoin as an example, traders can have multiple addresses, and these addresses have nothing to do with their identities in real life, their identities are difficult to identify, and it is difficult to track the flow of transaction funds on the blockchain. This paper proposes a transaction tracking system that can effectively and accurately track the source and destination of a certain amount of funds on the blockchain, which is superior to existing Bitcoin transaction tracking methods and has a substantial reference value.

Lambert T. Leong

The purpose of this work was to perform a network analysis on the rapidly\ngrowing bitcoin transaction network. Using a web-socket API, we collected data\non all transactions occurring during a six hour window. Sender and receiver\naddresses as well as the amount of bitcoin exchanged were record. Graphs were\ngenerated, using R and Gephi, in which nodes represent addresses and edges\nrepresent the exchange of bitcoin. The six hour data set was subsetted into a\none and two hour sampling snapshot of the network. We performed comparisons and\nanalysis on all subsets of the data in an effort to determine the minimum\nsampling length that represented the network as a whole. Our results suggest\nthat the six hour sampling was the minimum limit with respect to sampling time\nneeded to accurately characterize the bitcoin transaction network.Anonymity is\na desired feature of the blockchain and bitcoin network however, it limited us\nin our analysis and conclusions we drew from our results were mostly inferred.\nFuture work is needed and being done to gather more comprehensive data so that\nthe bitcoin transaction network can be better analyzed.\n

Yuriy Marchenko, William J. Knottenbelt, Katinka Wolter

No abstract is available for this record.

Natkamon Tovanich, Nicolas Heulot, Jean‐Daniel Fekete, Petra Isenberg

We present a systematic review of visual analytics tools used for the analysis of blockchains-related data. The blockchain concept has recently received considerable attention and spurred applications in a variety of domains. We systematically and quantitatively assessed 76 analytics tools that have been proposed in research as well as online by professionals and blockchain enthusiasts. Our classification of these tools distinguishes (1) target blockchains, (2) blockchain data, (3) target audiences, (4) task domains, and (5) visualization types. Furthermore, we look at which aspects of blockchain data have already been explored and point out areas that deserve more investigation in the future.

Christoph Kinkeldey, Jean‐Daniel Fekete, Tanja Blascheck, Petra Isenberg

We present BitConduite, a visual analytics tool for explorative analysis of financial activity within the Bitcoin network. Bitcoin is the largest cryptocurrency worldwide and a phenomenon that challenges the underpinnings of traditional financial systems - its users can send money pseudo-anonymously while circumventing traditional banking systems. Yet, despite the fact that all financial transactions in Bitcoin are available in an openly accessible online ledger - the blockchain - not much is known about how different types of actors in the network (we call them entities) actually use Bitcoin. BitConduite offers an entity-centered view on transactions, making the data accessible to non-technical experts through a guided workflow for classification of entities according to several activity metrics. Other novelties are the possibility to cluster entities by similarity and exploration of transaction data at different scales, from large groups of entities down to a single entity and the associated transactions. Two use cases illustrate the workflow of the system and its analytic power. We report on feedback regarding the approach and the the software tool gathered during a workshop with domain experts, and we discuss the potential of the approach based on our findings.

Andrew Burnie, Emine Yılmaz

We develop a new approach to temporalizing word2vec-based topic modelling that determines which topics on social media vary with shifts in the phases of a time series to understand potential interactions. This is particularly relevant for the highly volatile bitcoin price with its distinct four phases across 2017-18. We statistically test which words change in frequency between the different stages and compare four word2vec models to assess their consistency in relating connected words in weighted, undirected graphs. For words that fall in frequency when prices shift from rising to falling, all eight topics are identified with the four approaches; for words rising in frequency, three out of the five topics remain constant. These topics are intuitive and match with actual events in the news.

Yujing Sun, Hao Xiong, Siu Ming Yiu, Kwok‐Yan Lam

As an emerging payment method, bitcoin is receiving growing popularity for the different characteristics it shares with conventional fiat currencies. But the pseudonymous nature of bitcoin brings difficulties for regulators to effectively monitor bitcoin-related financial crimes. In this paper, we present an interactive system to visualize the relationship between bitcoin accounts, namely BitVis. With BitVis, users can easily filter transactions on demand, interact with the transaction networks to look for useful information, and analyze behavior of bitcoin accounts. Via BitVis, financial regulators can conveniently track suspicious accounts, while personal investors can easily investigate the activities of an interested account.

Silivanxay Phetsouvanh

Anwitaman Datta for his continuous support during my Ph.D. studies. His patient guidance, encouragement, and immense knowledge are precious to me and beyond what words can express. I really appreciate having a