36,908 research outputs found
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
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
Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles
How different cultures evaluate a person? Is an important person in one
culture is also important in the other culture? We address these questions via
ranking of multilingual Wikipedia articles. With three ranking algorithms based
on network structure of Wikipedia, we assign ranking to all articles in 9
multilingual editions of Wikipedia and investigate general ranking structure of
PageRank, CheiRank and 2DRank. In particular, we focus on articles related to
persons, identify top 30 persons for each rank among different editions and
analyze distinctions of their distributions over activity fields such as
politics, art, science, religion, sport for each edition. We find that local
heroes are dominant but also global heroes exist and create an effective
network representing entanglement of cultures. The Google matrix analysis of
network of cultures shows signs of the Zipf law distribution. This approach
allows to examine diversity and shared characteristics of knowledge
organization between cultures. The developed computational, data driven
approach highlights cultural interconnections in a new perspective.Comment: Published in PLoS ONE
(http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0074554).
Supporting information is available on the same webpag
First Women, Second Sex: Gender Bias in Wikipedia
Contributing to history has never been as easy as it is today. Anyone with
access to the Web is able to play a part on Wikipedia, an open and free
encyclopedia. Wikipedia, available in many languages, is one of the most
visited websites in the world and arguably one of the primary sources of
knowledge on the Web. However, not everyone is contributing to Wikipedia from a
diversity point of view; several groups are severely underrepresented. One of
those groups is women, who make up approximately 16% of the current contributor
community, meaning that most of the content is written by men. In addition,
although there are specific guidelines of verifiability, notability, and
neutral point of view that must be adhered by Wikipedia content, these
guidelines are supervised and enforced by men.
In this paper, we propose that gender bias is not about participation and
representation only, but also about characterization of women. We approach the
analysis of gender bias by defining a methodology for comparing the
characterizations of men and women in biographies in three aspects: meta-data,
language, and network structure. Our results show that, indeed, there are
differences in characterization and structure. Some of these differences are
reflected from the off-line world documented by Wikipedia, but other
differences can be attributed to gender bias in Wikipedia content. We
contextualize these differences in feminist theory and discuss their
implications for Wikipedia policy.Comment: 10 pages, ACM style. Author's version of a paper to be presented at
ACM Hypertext 201
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
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The afterlife of 'living deliverables': angels or zombies?
Within the STELLAR project, we provide the possibility to use living documents for the collaborative writing work on deliverables. Compared to 'normal' deliverables, 'living' deliverables come into existence much earlier than their delivery deadline and are expected to 'live on' after their official delivery to the European Commission. They are expected to foster collaboration. Within this contribution we investigate, how these deliverables have been used over the first 16 months of the project. We therefore propose a set of new analysis methods facilitating social network analysis on publicly available revision history data. With this instrumentarium, we critically look at whether the living deliverables have been successfully used for collaboration and whether their 'afterlife' beyond the contractual deadline had turned them into 'zombies' (still visible, but no or little live editing activities). The results show that the observed deliverables show signs of life, but often in connection with a topical change and in conjunction with changes in the pattern of collaboration
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
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