30,185 research outputs found
The Network Structure of Successful Collaboration in Wikipedia
Wikipedia is one of the largest and most successful examples of decentralized peer-production systems currently in existence. Yet, the quality of Wikipedia articles varies widely with articles considered of encyclopedic quality (called featured articles) representing less than 0.1 percent of all articles. In this paper, we examine how article quality varies as a function of the network mechanisms that control the interaction among contributors. More specifically, we compare the network mechanisms underlying the production of the complete set of featured articles, with the network mechanisms of a contrasting sample of comparable non-featured articles in the English-language edition of Wikipedia. Estimates of relational event models suggest that contributors to featured articles display greater deference toward the reputation of their team members. Contributors to featured articles also display a weaker tendency to follow the behavioral norms predicted by the theory of structural balance, and hence a weaker tendency toward polarization
Network Structure, Efficiency, and Performance in WikiProjects
The internet has enabled collaborations at a scale never before possible, but
the best practices for organizing such large collaborations are still not
clear. Wikipedia is a visible and successful example of such a collaboration
which might offer insight into what makes large-scale, decentralized
collaborations successful. We analyze the relationship between the structural
properties of WikiProject coeditor networks and the performance and efficiency
of those projects. We confirm the existence of an overall
performance-efficiency trade-off, while observing that some projects are higher
than others in both performance and efficiency, suggesting the existence
factors correlating positively with both. Namely, we find an association
between low-degree coeditor networks and both high performance and high
efficiency. We also confirm results seen in previous numerical and small-scale
lab studies: higher performance with less skewed node distributions, and higher
performance with shorter path lengths. We use agent-based models to explore
possible mechanisms for degree-dependent performance and efficiency. We present
a novel local-majority learning strategy designed to satisfy properties of
real-world collaborations. The local-majority strategy as well as a localized
conformity-based strategy both show degree-dependent performance and
efficiency, but in opposite directions, suggesting that these factors depend on
both network structure and learning strategy. Our results suggest possible
benefits to decentralized collaborations made of smaller, more tightly-knit
teams, and that these benefits may be modulated by the particular learning
strategies in use.Comment: 11 pages, 5 figures, to appear in ICWSM 201
Exploring the Relationship between Membership Turnover and Productivity in Online Communities
One of the more disruptive reforms associated with the modern Internet is the
emergence of online communities working together on knowledge artefacts such as
Wikipedia and OpenStreetMap. Recently it has become clear that these
initiatives are vulnerable because of problems with membership turnover. This
study presents a longitudinal analysis of 891 WikiProjects where we model the
impact of member turnover and social capital losses on project productivity. By
examining social capital losses we attempt to provide a more nuanced analysis
of member turnover. In this context social capital is modelled from a social
network perspective where the loss of more central members has more impact. We
find that only a small proportion of WikiProjects are in a relatively healthy
state with low levels of membership turnover and social capital losses. The
results show that the relationship between social capital losses and project
performance is U-shaped, and that member withdrawal has significant negative
effect on project outcomes. The results also support the mediation of turnover
rate and network density on the curvilinear relationship
Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists
Scientific collaborations shape ideas as well as innovations and are both the
substrate for, and the outcome of, academic careers. Recent studies show that
gender inequality is still present in many scientific practices ranging from
hiring to peer-review processes and grant applications. In this work, we
investigate gender-specific differences in collaboration patterns of more than
one million computer scientists over the course of 47 years. We explore how
these patterns change over years and career ages and how they impact scientific
success. Our results highlight that successful male and female scientists
reveal the same collaboration patterns: compared to scientists in the same
career age, they tend to collaborate with more colleagues than other
scientists, seek innovations as brokers and establish longer-lasting and more
repetitive collaborations. However, women are on average less likely to adapt
the collaboration patterns that are related with success, more likely to embed
into ego networks devoid of structural holes, and they exhibit stronger gender
homophily as well as a consistently higher dropout rate than men in all career
ages
The Evolution of Wikipedia's Norm Network
Social norms have traditionally been difficult to quantify. In any particular
society, their sheer number and complex interdependencies often limit a
system-level analysis. One exception is that of the network of norms that
sustain the online Wikipedia community. We study the fifteen-year evolution of
this network using the interconnected set of pages that establish, describe,
and interpret the community's norms. Despite Wikipedia's reputation for
\textit{ad hoc} governance, we find that its normative evolution is highly
conservative. The earliest users create norms that both dominate the network
and persist over time. These core norms govern both content and interpersonal
interactions using abstract principles such as neutrality, verifiability, and
assume good faith. As the network grows, norm neighborhoods decouple
topologically from each other, while increasing in semantic coherence. Taken
together, these results suggest that the evolution of Wikipedia's norm network
is akin to bureaucratic systems that predate the information age.Comment: 22 pages, 9 figures. Matches published version. Data available at
http://bit.ly/wiki_nor
Mapping bilateral information interests using the activity of Wikipedia editors
We live in a global village where electronic communication has eliminated the
geographical barriers of information exchange. The road is now open to
worldwide convergence of information interests, shared values, and
understanding. Nevertheless, interests still vary between countries around the
world. This raises important questions about what today's world map of in-
formation interests actually looks like and what factors cause the barriers of
information exchange between countries. To quantitatively construct a world map
of information interests, we devise a scalable statistical model that
identifies countries with similar information interests and measures the
countries' bilateral similarities. From the similarities we connect countries
in a global network and find that countries can be mapped into 18 clusters with
similar information interests. Through regression we find that language and
religion best explain the strength of the bilateral ties and formation of
clusters. Our findings provide a quantitative basis for further studies to
better understand the complex interplay between shared interests and conflict
on a global scale. The methodology can also be extended to track changes over
time and capture important trends in global information exchange.Comment: 11 pages, 3 figures in Palgrave Communications 1 (2015
Temporal Analysis of Activity Patterns of Editors in Collaborative Mapping Project of OpenStreetMap
In the recent years Wikis have become an attractive platform for social
studies of the human behaviour. Containing millions records of edits across the
globe, collaborative systems such as Wikipedia have allowed researchers to gain
a better understanding of editors participation and their activity patterns.
However, contributions made to Geo-wikis_wiki-based collaborative mapping
projects_ differ from systems such as Wikipedia in a fundamental way due to
spatial dimension of the content that limits the contributors to a set of those
who posses local knowledge about a specific area and therefore cross-platform
studies and comparisons are required to build a comprehensive image of online
open collaboration phenomena. In this work, we study the temporal behavioural
pattern of OpenStreetMap editors, a successful example of geo-wiki, for two
European capital cities. We categorise different type of temporal patterns and
report on the historical trend within a period of 7 years of the project age.
We also draw a comparison with the previously observed editing activity
patterns of Wikipedia.Comment: Submitte
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