scholarly journals Participation in wiki communities: reconsidering their statistical characterization

2021 ◽  
Vol 8 ◽  
pp. e792
Author(s):  
Ámbar Tenorio-Fornés ◽  
Javier Arroyo ◽  
Samer Hassan

Peer production online communities are groups of people that collaboratively engage in the building of common resources such as wikis and open source projects. In such communities, participation is highly unequal: few people concentrate the majority of the workload, while the rest provide irregular and sporadic contributions. The distribution of participation is typically characterized as a power law distribution. However, recent statistical studies on empirical data have challenged the power law dominance in other domains. This work critically examines the assumption that the distribution of participation in wikis follows such distribution. We use statistical tools to analyse over 6,000 wikis from Wikia/Fandom, the largest wiki repository. We study the empirical distribution of each wiki comparing it with different well-known skewed distributions. The results show that the power law performs poorly, surpassed by three others with a more moderated heavy-tail behavior. In particular, the truncated power law is superior to all competing distributions, or superior to some and as good as the rest, in 99.3% of the cases. These findings have implications that can inform a better modeling of participation in peer production, and help to produce more accurate predictions of the tail behavior, which represents the activity and frequency of the core contributors. Thus, we propose to consider the truncated power law as the distribution to characterize participation distribution in wiki communities. Furthermore, the truncated power law parameters provide a meaningful interpretation to characterize the community in terms of the frequency of participation of occasional contributors and how unequal are the group of core contributors. Finally, we found a relationship between the parameters and the productivity of the community and its size. These results open research venues for the characterization of communities in wikis and in online peer production.

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Amir Pasha Motamed ◽  
Behnam Bahrak

AbstractCryptocurrencies as a new way of transferring assets and securing financial transactions have gained popularity in recent years. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin, with no comprehensive comparison between these currencies. In this study, we intend to compare the transaction graph of Bitcoin, Ethereum, Litecoin, Dash, and Z-Cash, with respect to the dynamics of their transaction graphs over time, and discuss their properties. In particular, we observed that the growth rate of the nodes and edges of the transaction graphs, and the density of these graphs, are closely related to the price of these currencies. We also found that the transaction graph of these currencies is non-assortative, i.e. addresses do not tend for transact with a particular type of addresses of higher or lower degree, and the degree sequence of their transaction graph follows the power law distribution.


Author(s):  
Ken Oliphant ◽  
Wayne Bryce ◽  
William Luff

When major pipeline incidents occur there is always a question as to how applicable the learnings from that incident are across the industry. To address this question for the San Bruno pipeline failure in 2010, an analysis of historical transmission pipeline industry events was conducted to determine if San Bruno was consistent with past industry performance or whether it was an outlier event. This paper draws on Power Law analysis to generate a characteristic curve of past transmission pipeline accidents in the US. Power Law, or Pareto, behavior has been observed for a wide variety of phenomenon, such as fire damage, earthquake damage and terrorist attacks. The size of these events is seen to follow not the typical normal distribution but the Power Law distribution, where low probability - high consequence (LPHC) events play a more significant role in the overall risk picture. Analysis shows that the consequences of pipeline incidents in a variety of pipeline industries (gas distribution, gas transmission, gas gathering and hazardous liquid pipelines) are seen to exhibit Power Law behavior. The Power Law model is seen to capture the distribution of the size of consequences from pipeline incidents and defines the relationship between the size of an incident and its frequency. Through characterization of these distributions, it is possible to project the likelihood or expected frequency of events of a given magnitude and to assess if a given incident fits within historical industry patterns; i.e. whether the incident is consistent with past observations or is an outlier. The Power Law analysis shows that the San Bruno incident, which caused eight fatalities and an estimated $380 million in property damage in 2010, is not an outlier. Rather, this incident lies on the Power Law curve for historical transmission pipeline incidents, with an estimated frequency of once every 40 years. The event is consistent with the history of gas transmission pipeline consequences in the US. This paper argues that the San Bruno incident, therefore, provides lessons relevant to the industry as whole.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Evangelos Mitsokapas ◽  
Benjamin Schäfer ◽  
Rosemary J. Harris ◽  
Christian Beck

AbstractThe aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.


2020 ◽  
Author(s):  
Evangelos Mitsokapas ◽  
Benjamin Schäfer ◽  
Rosemary Harris ◽  
Christian Beck

Abstract The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.


1985 ◽  
Vol 25 (01) ◽  
pp. 39-45 ◽  
Author(s):  
Dominique Guillot ◽  
Alain Dunand

Abstract In this paper we describe the use of a novel technique, laser Doppler anemometry (LDA), to obtain information on fracturing fluid behavior. This technique permits measurement of fluid velocity at any point in a flow system. By scanning across the flow geometry, it is possible to obtain the velocity profile, which is related, possible to obtain the velocity profile, which is related, in turn, to the rheology of the fluid. At low shear rates, velocity profiles obtained for aqueous solutions of hydroxypropyl guar showed significant deviations from those calculated using known power law parameters. The investigation was extended by power law parameters. The investigation was extended by conducting a series of rheological experiments using rotational and capillary viscometers over a wide shear-rate range (10(–2) to 2 × 10(3) seconds (–1)) The data have been fitted to a three-parameter Ellis model, and the velocity profiles calculated from these data agree well with profiles calculated from these data agree well with experimental ones. The immediate results of this work are of interest in proppant transport modeling and correlate well with proppant transport modeling and correlate well with published data that show that apparent viscosities obtained published data that show that apparent viscosities obtained from proppant settling velocities are lower than those obtained from power law parameters. Introduction The role played by the rheology of fracturing fluids in the design of stimulation treatments does not need to be stressed. Friction pressure through pipes and/or annuli, fracture geometry, and proppant placement depend primarily on the rheological properties of treating fluids. primarily on the rheological properties of treating fluids. Fracturing fluids usually exhibit a non-Newtonian behavior. Under isothermal conditions, their rheological properties may be shear-dependent only, as in linear gels, properties may be shear-dependent only, as in linear gels, or much more complex (i.e., time/shear-dependent), as in the case of crosslinked gels. Several types of rheometers have been used to characterize the behavior of fracturing fluids: coaxial cylinder viscometers, cone and plate rheometers, and capillary viscometers. These traditional means of evaluating non-Newtonian rheology are subject to several drawbacks inherent in the measuring technique itself or in the type of fluid under study. For instance, coaxial cylinder and capillary viscometers do not allow for the direct computation of the shear rate that is applied to measured fluids. For a time-independent non-Newtonian fluid, a proper interpretation of the measurements must involve the determination of the first, or even higher order, derivative of the experimental curve Copyright 1985 Society of Petroleum Engineers (rotational speed/torque or flow-rate/pressure-drop curves). The time-dependent nature of some fluids complicates the problem, since, in these viscometers, fluid particles experience different shear rates and, therefore, particles experience different shear rates and, therefore, different shear histories. On the experimental side, difficulties may arise from the three-dimensional structure and from the correlative elasticity of crosslinked fluids-e.g., the Weissenberg effect in coaxial cylinder viscometers or the ejection of the fluid from cone and plate rheometers in steady rotation even at low speeds. Some of the limitations encountered in the rheological characterization of time-dependent fracturing fluids may be overcome with an improved experimental techniqueLDA. LDA is a direct and nondestructive technique for measuring particle velocities in a moving fluid. Therefore, it allows characterization of the flow kinematics. The technique was tested first on the simplest case of a time-independent fluid to evaluate its validity for fracturing rheological studies. In the following sections, after a description of the LDA technique and of the equipment, we illustrate the use of the LDA by the study of a noncrosslinked fluid that has been characterized using classical rheometrical methods. We stress the importance of the frequently forgotten Newtonian behavior of these linear gels at low shear rates. Implication of the results on the design of fracturing treatments also is discussed. The LDA Technique Principle LDA uses the Doppler shift of light scattered Principle. LDA uses the Doppler shift of light scattered by moving particles in a flow system to determine particle velocity and thus measure the fluid velocity at a given point. In dual-beam mode, the most common technique, two point. In dual-beam mode, the most common technique, two coherent laser beams of equal intensity intersect, and light scattered in any one direction is picked up by a photodetector (Fig. 1). The difference, fD, between the photodetector (Fig. 1). The difference, fD, between the two scattering frequencies, fsi and fs2 is independent of the scattering direction, es, and proportional to a velocity component, Vx, of the particles flowing through the beam intersection (Fig. 2). LDA has the great advantage of being a direct and nonperturbative velocimetry technique in that only light beams enter the flow through a transparent window. No flow calibration is required, and no probe (hot wire, turbine) is necessary inside the flow, thereby eliminating any disturbances. SPEJ P. 39


2009 ◽  
Vol 99 (4) ◽  
pp. 1672-1675 ◽  
Author(s):  
Moshe Levy

Jan Eeckhout (2004) reports that the empirical city size distribution is lognormal, consistent with Gibrat's Law. We show that for the top 0.6 percent of the largest cities, the empirical distribution is dramatically different from the lognormal, and follows a power law. This top part is extremely important as it accounts for more than 23 percent of the population. The empirical hybrid lognormal-power-law distribution revealed may be characteristic of other key distributions, such as the wealth distribution and the income distribution. This distribution is not consistent with a simple Gibrat proportionate effect process, and its origin presents a puzzle yet to be answered. (JEL R11, R12, R23)


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.


2021 ◽  
Author(s):  
David A Garcia ◽  
Gregory Fettweis ◽  
Diego M Presman ◽  
Ville Paakinaho ◽  
Christopher Jarzynski ◽  
...  

Abstract Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs—one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.


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