277 research outputs found
Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performance
The production and consumption of information about Bitcoin and other digital-, or 'crypto'-, currencies have grown together with their market capitalisation. However, a systematic investigation of the relationship between online attention and market dynamics, across multiple digital currencies, is still lacking. Here, we quantify the interplay between the attention towards digital currencies in Wikipedia and their market performance. We consider the entire edit history of currency-related pages, and their view history from July 2015. First, we quantify the evolution of the cryptocurrency presence in Wikipedia by analysing the editorial activity and the network of co-edited pages. We find that a small community of tightly connected editors is responsible for most of the production of information about cryptocurrencies in Wikipedia. Then, we show that a simple trading strategy informed by Wikipedia views performs better, in terms of returns on investment, than classic baseline strategies for most of the covered period. Our results contribute to the recent literature on the interplay between online information and investment markets, and we anticipate it will be of interest for researchers as well as investors
Consequence of reputation in an open-ended Naming Game
We study a modified version of the Naming Game, a recently introduced model
which describes how shared vocabulary can emerge spontaneously in a population
without any central control. In particular, we introduce a new mechanism that
allows a continuous interchange with the external inventory of words. A novel
playing strategy, influenced by the hierarchical structure that individuals'
reputation defines in the community, is implemented. We analyze how these
features influence the convergence times, the cognitive efforts of the agents
and the scaling behavior in memory and time.Comment: 6 pages, 6 figure
Recommended from our members
Machine Learning meets Number Theory: The Data Science of Birch-Swinnerton-Dyer
Empirical analysis is often the first step towards the birth of a conjecture. This is the case of the Birch-Swinnerton-Dyer (BSD) Conjecture describing the rational points on an elliptic curve, one of the most celebrated unsolved problems in mathematics. Here we extend the original empirical approach, to the analysis of the Cremona database of quantities relevant to BSD, inspecting more than 2.5 million elliptic curves by means of the latest techniques in data science, machine-learning and topological data analysis. Key quantities such as rank, Weierstrass coefficients, period, conductor, Tamagawa number, regulator and order of the Tate-Shafarevich group give rise to a high-dimensional point-cloud whose statistical properties we investigate. We reveal patterns and distributions in the rank versus Weierstrass coefficients, as well as the Beta distribution of the BSD ratio of the quantities. Via gradient boosted trees, machine learning is applied in finding inter-correlation amongst the various quantities. We anticipate that our approach will spark further research on the statistical properties of large datasets in Number Theory and more in general in pure Mathematics
Microscopic activity patterns in the Naming Game
The models of statistical physics used to study collective phenomena in some
interdisciplinary contexts, such as social dynamics and opinion spreading, do
not consider the effects of the memory on individual decision processes. On the
contrary, in the Naming Game, a recently proposed model of Language formation,
each agent chooses a particular state, or opinion, by means of a memory-based
negotiation process, during which a variable number of states is collected and
kept in memory. In this perspective, the statistical features of the number of
states collected by the agents becomes a relevant quantity to understand the
dynamics of the model, and the influence of topological properties on
memory-based models. By means of a master equation approach, we analyze the
internal agent dynamics of Naming Game in populations embedded on networks,
finding that it strongly depends on very general topological properties of the
system (e.g. average and fluctuations of the degree). However, the influence of
topological properties on the microscopic individual dynamics is a general
phenomenon that should characterize all those social interactions that can be
modeled by memory-based negotiation processes.Comment: submitted to J. Phys.
Collective Dynamics of Dark Web Marketplaces
Dark markets are commercial websites that use Bitcoin to sell or broker transactions involving drugs, weapons, and other illicit goods. Being illegal, they do not offer any user protection, and several police raids and scams have caused large losses to both customers and vendors over the past years. However, this uncertainty has not prevented a steady growth of the dark market phenomenon and a proliferation of new markets. The origin of this resilience have remained unclear so far, also due to the difficulty of identifying relevant Bitcoin transaction data. Here, we investigate how the dark market ecosystem re-organises following the disappearance of a market, due to factors including raids and scams. To do so, we analyse 24 episodes of unexpected market closure through a novel datasets of 133 million Bitcoin transactions involving 31 dark markets and their users, totalling 4 billion USD. We show that coordinated user migration from the closed market to coexisting markets guarantees overall systemic resilience beyond the intrinsic fragility of individual markets. The migration is swift, efficient and common to all market closures. We find that migrants are on average more active users in comparison to non-migrants and move preferentially towards the coexisting market with the highest trading volume. Our findings shed light on the resilience of the dark market ecosystem and we anticipate that they may inform future research on the self-organisation of emerging online markets
Modeling the emergence of a new language: Naming Game with hybridization
In recent times, the research field of language dynamics has focused on the
investigation of language evolution, dividing the work in three evolutive
steps, according to the level of complexity: lexicon, categories and grammar.
The Naming Game is a simple model capable of accounting for the emergence of a
lexicon, intended as the set of words through which objects are named. We
introduce a stochastic modification of the Naming Game model with the aim of
characterizing the emergence of a new language as the result of the interaction
of agents. We fix the initial phase by splitting the population in two sets
speaking either language A or B. Whenever the result of the interaction of two
individuals results in an agent able to speak both A and B, we introduce a
finite probability that this state turns into a new idiom C, so to mimic a sort
of hybridization process. We study the system in the space of parameters
defining the interaction, and show that the proposed model displays a rich
variety of behaviours, despite the simple mean field topology of interactions.Comment: 12 pages, 10 figures, presented at IWSOS 2013 Palma de Mallorca, the
final publication will be available at LNCS http://www.springer.com/lnc
In-depth analysis of the Naming Game dynamics: the homogeneous mixing case
Language emergence and evolution has recently gained growing attention
through multi-agent models and mathematical frameworks to study their behavior.
Here we investigate further the Naming Game, a model able to account for the
emergence of a shared vocabulary of form-meaning associations through
social/cultural learning. Due to the simplicity of both the structure of the
agents and their interaction rules, the dynamics of this model can be analyzed
in great detail using numerical simulations and analytical arguments. This
paper first reviews some existing results and then presents a new overall
understanding.Comment: 30 pages, 19 figures (few in reduced definition). In press in IJMP
Recommended from our members
The role of topology on the dynamics of the Naming Game
The Naming Game captures the essential features leading a population to agree on the use of a semiotic convention (or, more in general, an opinion). Consensus emerges through local negotiations between pairs of agents, in the absence of any central co-ordination. Thus, it is natural that topology, identifying the set of possible interactions, plays a central role in the dynamics of the model. Here, we review the role of different topological properties, pointing out that finite connectivity, combined with the small-world property, ensure the best performances in terms of memory usage and time to reach convergence
Recommended from our members
On the relation between Transversal and Longitudinal Scaling in Cities
Given that a group of cities follows a scaling law connecting urban population with socio-economic or infrastructural metrics (transversal scaling), should we expect that each city would follow the same behavior over time (longitudinal scaling)? This assumption has important policy implications, although rigorous empirical tests have been so far hindered by the lack of suitable data. Here, we advance the debate by looking into the temporal evolution of the scaling laws for 5507 municipalities in Brazil. We focus on the relationship between population size and two urban variables, GDP and water network length, analyzing the time evolution of the system of cities as well as their individual trajectory. We find that longitudinal (individual) scaling exponents are city-specific, but they are distributed around an average value that approaches to the transversal scaling exponent when the data are decomposed to eliminate external factors, and when we only consider cities with a sufficiently large growth rate. Such results give support to the idea that the longitudinal dynamics is a micro-scaling version of the transversal dynamics of the entire urban system. Finally, we propose a mathematical framework that connects the microscopic level to global behavior, and, in all analyzed cases, we find good agreement between theoretical prediction and empirical evidence
Recommended from our members
Individual mobility and social behaviour: Two sides of the same coin
According to personality psychology, personality traits determine many aspects of human behaviour. However, validating this insight in large groups has been challenging so far, due to the scarcity of multi-channel data. Here, we focus on the relationship between mobility and social behaviour by analysing two high-resolution longitudinal datasets collecting trajectories and mobile phone interactions of individuals. We show that there is a connection between the way in which individuals explore new resources and exploit known assets in the social and spatial spheres. We point out that different individuals balance the exploration-exploitation trade-off in different ways and we explain part of the variability in the data by the big five personality traits. We find that, in both realms, extraversion correlates with an individual's attitude towards exploration and routine diversity, while neuroticism and openness account for the tendency to evolve routine over long time-scales. We find no evidence for the existence of classes of individuals across the spatio-social domains. Our results bridge the fields of human geography, sociology and personality psychology and can help improve current models of mobility and tie formation
- …