BLOCKCHAIN AND FINTECH NETWORK SCIENCE
Bitcoin is a digital asset designed to work as a medium of exchange. Users can send and receive native tokens - the ‘bitcoins’ - while collectively validating the transactions in a decentralized and transparent network. After Bitcoin appeared in 2009, approximately 1,500 cryptocurrencies have been introduced, around 800 of which are actively traded today. All cryptocurrencies share the underlying blockchain technology, but implement different mechanisms of consensus.
Although the aggregated values of cryptocurrencies has exploded in 2017, reaching $180 billion, few studies have so far put to use Network Science to address the full complexity of the system at different scales. The goal of the present workshop is to bring together pioneers of this approach and to illustrate the diversity of variety of challenges that the system poses to a broader audience of Network Scientists. Blockchain-based systems provide a fertile ground for the application of Network Science’s theoretical and computational tools to conceive systems more robust and resilient to overload or designed attacks, as well as to enhance and protect user’s anonymity from profiling and identification.
The scope of the satellite meeting is to review the recent advances in the application of network science to blockchain technologies and cryptocurrencies in general. We will pay special attention to novel applications in which the network analysis, topology or dynamics play a crucial role. The spectrum that we aim to cover at the conference include, but is not restricted to, the following topics:
1. Structure and dynamics of the cryptocurrency market
2. Network modeling and analysis of crytopcurrency transaction graphs
3. Robustness and resilience of blockchain networks to network-based attacks
4. Deanonymization techniques
5. Algorithms/Protocols of distributed consensus
6. Social media and sentiment analysis of the Blockchain debate
7. Interactive tools for analysis of transaction networks
City, University of London
Fondazione Bruno Kessler
University of Zurich
|8 January 2018||Call for abstracts|
|15 March 2018||Deadline for abstract submission|
|1 April 2018||Notification of acceptance|
|11 June 2018||Satellite event|
Evolutionary dynamics of the cryptocurrencies market
Earlier this year the cryptocurrency market surpassed the barrier of $800 billion market capitalization, however, in less than two months the market lost more than $400 billion of its value. Despite its increasing relevance in the fi- nancial world, a comprehensive analysis of the whole system is still lacking, since most of the studies have focused exclusively on the behaviour of one (Bit- coin) or few cryptocurrencies. In this work, we consider the history of the entire market and analyse the behaviour of 1469 cryptocurrencies introduced between April 2013 and May 2017. We reveal that, while new cryptocurrencies appear and disappear continuously and their market capitalization is increas- ing (super-)exponentially, several statistical properties of the market have been stable for years. These include the number of active cryptocurrencies, market share distribution and the turnover of cryptocurrencies. Adopting an ecological perspective, we show that the so-called neutral model of evolution is able to reproduce a number of key empirical observations, despite its simplicity and the assumption of no selective advantage of one cryptocurrency over another. Our results shed light on the properties of the cryptocurrency market and establish a first formal link between ecological modelling and the study of this growing system. We anticipate they will spark further research in this direction.
Analyzing Bitcoin Transactions as a Link Stream
The public recording of all financial transactions performed in Bitcoins opens great opportunities to understand the structure and dynamics of such transactions. This raises two challenges, though. First, one has to preprocess the raw data in order to identify wallets susceptible to belong to the same (group of) individual(s). Several heuristics exist for this and we will overview their strengths and weaknesses in this presentation. Second, such data call for an appropriate modeling of transactions in order to capture their both temporal and structural nature. The stream graph and link stream formalism makes this possible by merging time series and graph points of views. We present in this talk a first analysis of Bitcoin transactions conducted with this approach.
Quantifying economic activity on financial transaction networks
Banks, FinTech companies, and distributed legers all host systems that record financial transaction data as a temporal network. This work presents a measure of overall economic activity on these systems, and calculates this measure over time for a particularly novel financial system - mobile money.”
Analysis of the Bitcoin blockchain: Socio-economic factors behind the adoption
As the first decentralized digital currency introduced in 2009 together with the blockchain, Bitcoin offers new opportunities both for developed and developing countries. Bitcoin peer-to-peer transactions are independent of the banking system, thus facilitating foreign exchanges with low transaction fees such as remittances, with a high degree of anonymity. These opportunities together with other key factors led the Bitcoin to become extremely popular and made its price skyrocket during 2017.
However, while the Bitcoin blockchain attracts a lot of attention, it remains difficult to investigate where this attention comes from, due to the pseudo-anonymity of the system, and consequently to appreciate its social impact. Here we make an attempt to characterize the adoption of the bitcoin blockchain by country. In the first part of the work we show that information about the number of Bitcoin software client downloads, the IP addresses that act as relays for the transactions, and the Internet searches about Bitcoin provide together a coherent picture of the system evolution in different countries. Using these quantities as a proxy for user adoption, we identified several socio-economic indexes such as the GDP per capita, freedom of trade and the Internet penetration as key variables correlated with the degree of user adoption. In the second part of the work, we build a network of Bitcoin transactions between countries using the IP addresses of nodes relaying transactions and we develop an augmented version of the gravity model of trade in order to identify socio-economic factors linked to the flow of Bitcoin between countries.
The paths to centralisation in blockchain-based systems
Blockchain has disrupted the way of thinking decentralised systems: This mechanism allows the secure diffusion of information across a network without the need of a central (trusted) authority to enforce the emergence of consensus in the information that is exchanged and stored by its participants. Indeed, as a primary example, the digital currency Bitcoin is implemented on top of a blockchain, and its value is solely assigned by a (largely speculative) market. This talk is divided into two parts. First, the analysis of Bitcoin as a closed economy: having followed a technocratic approach in its immutable design, it is the only case of an economy where all monetary transactions can be traced back with full detail. Interestingly, its fixed incentive scheme has created the emergence of large levels of centralisation and economic flow, drastically different from its original conception. The second part of the presentation is about consensus in blockchain-based systems. While in the last years the number of its applications has increased enormously, little is known about their suitability in stressed working conditions. We introduce a stochastic modelling approach (an extension of the celebrated compartmental models) for these systems, identifying a phase transition from efficient consensus in the diffusion of information to a frustrated (congested) state where the information flow rapidly deteriorates.
Marco Alberto Javarone
Emerging Patterns in the Bitcoin Network
We investigate the topological features of some Bitcoin and Bitcoin Cash Networks. Notably, we aim to understand if their emergence and evolution can be described by some well defined stochastic process, considering the heterogeneity of nodes taking part to these systems. It is worth to highlight that this preliminary analysis provides interesting clues for assessing if these networks are 'small-world'.
The interplay between network structure and market effects in Bitcoin
We reconstruct the network of transactions and extract the time and amount of each payment. We analyze the structure of the transaction network by measuring network characteristics over time, such as the degree distribution, degree correlations and clustering. We find that linear preferential attachment drives the growth of the network. We also study the dynamics taking place on the transaction network, i.e. the flow of money. We measure temporal patterns and the wealth accumulation. Investigating the microscopic statistics of money movement, we find that sublinear preferential attachment governs the evolution of the wealth distribution. We report a scaling law between the degree and wealth associated to individual nodes. We also analyze changes in the structure of the subgraph induced by the most active users. Our approach is based on the unsupervised identification of important features of the time variation of the network. Applying the widely used method of Principal Component Analysis to the matrix constructed from snapshots of the network at different times, we are able to show how structural changes in the network accompany significant changes in the exchange price of bitcoins.
Towards a scientific blockchain framework for reproducible data analysis
Publishing reproducible analyses is a long-standing and widespread challenge for the scientific community, funding bodies and publishers. Although a definitive solution is still elusive, the problem is recognized to affect all disciplines and lead to a critical system inefficiency. Here, we propose a blockchain-based approach to enhance scientific reproducibility, with a focus on life science studies and precision medicine. While the interest of encoding permanently into an immutable ledger all the study key information-including endpoints, data and metadata, protocols, analytical methods and all findings-has been already highlighted, here we apply the blockchain approach to solve the issue of rewarding time and expertise of scientists that commit to verify reproducibility. Our mechanism builds a trustless ecosystem of researchers, funding bodies and publishers cooperating to guarantee digital and permanent access to information and reproducible results. As a natural byproduct, a procedure to quantify scientists' and institutions' reputation for ranking purposes is obtained.
Radoslaw Michalski (joint work with Bartosz Zychal)
Blockchain as a Complex Network - the Analysis of Trends of Bitcoin Blockchain
In this talk we show how we analysed the bitcoin blockchain when trying to find out what are the topological trends in this complex network. Due to the fact that processing such a large graph is computationally challenging, we introduce a sampling method that links the transactions from separate blocks by combining all outputs leading to a chosen input transaction we start sampling from. Further, we investigate what kind of network structures emerge in network sampled in such a way and try to match these structures to entities such as mining pools or exchanges we found information about.
Manlio De Domenico