3,175 research outputs found
Are anonymity-seekers just like everybody else? An analysis of contributions to Wikipedia from Tor
User-generated content sites routinely block contributions from users of
privacy-enhancing proxies like Tor because of a perception that proxies are a
source of vandalism, spam, and abuse. Although these blocks might be effective,
collateral damage in the form of unrealized valuable contributions from
anonymity seekers is invisible. One of the largest and most important
user-generated content sites, Wikipedia, has attempted to block contributions
from Tor users since as early as 2005. We demonstrate that these blocks have
been imperfect and that thousands of attempts to edit on Wikipedia through Tor
have been successful. We draw upon several data sources and analytical
techniques to measure and describe the history of Tor editing on Wikipedia over
time and to compare contributions from Tor users to those from other groups of
Wikipedia users. Our analysis suggests that although Tor users who slip through
Wikipedia's ban contribute content that is more likely to be reverted and to
revert others, their contributions are otherwise similar in quality to those
from other unregistered participants and to the initial contributions of
registered users.Comment: To appear in the IEEE Symposium on Security & Privacy, May 202
Can Who-Edits-What Predict Edit Survival?
As the number of contributors to online peer-production systems grows, it
becomes increasingly important to predict whether the edits that users make
will eventually be beneficial to the project. Existing solutions either rely on
a user reputation system or consist of a highly specialized predictor that is
tailored to a specific peer-production system. In this work, we explore a
different point in the solution space that goes beyond user reputation but does
not involve any content-based feature of the edits. We view each edit as a game
between the editor and the component of the project. We posit that the
probability that an edit is accepted is a function of the editor's skill, of
the difficulty of editing the component and of a user-component interaction
term. Our model is broadly applicable, as it only requires observing data about
who makes an edit, what the edit affects and whether the edit survives or not.
We apply our model on Wikipedia and the Linux kernel, two examples of
large-scale peer-production systems, and we seek to understand whether it can
effectively predict edit survival: in both cases, we provide a positive answer.
Our approach significantly outperforms those based solely on user reputation
and bridges the gap with specialized predictors that use content-based
features. It is simple to implement, computationally inexpensive, and in
addition it enables us to discover interesting structure in the data.Comment: Accepted at KDD 201
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Similarities, challenges and opportunities of wikipedia content and open source projects
Copyright @ 2012 John Wiley & Sons, Ltd.Several years of research and evidence have demonstrated that Open Source Software (OSS) portals often contain a large amount of software projects that simply do not evolve, developed by relatively small communities, struggling to attract a sustained number of contributors. These portals have started to
increasingly act as a storage for abandoned projects, and researchers and practitioners should try and point out how to take advantage of such content. Similarly, other online content portals (like Wikipedia) could be harvested for valuable content. In this paper we argue that, even with differences in the requested expertise, many projects reliant on content and contributions by users undergo a similar evolution, and follow similar patterns: when a project fails to attract contributors, it appears to be not evolving, or abandoned. Far from a negative finding, even those projects could provide valuable content that should be harvested and identified based on common characteristics: by using the attributes of “usefulness” and “modularity” we isolate valuable content in both Wikipedia pages and OSS projects
A Wikipedia Literature Review
This paper was originally designed as a literature review for a doctoral
dissertation focusing on Wikipedia. This exposition gives the structure of
Wikipedia and the latest trends in Wikipedia research
Dynamics of conflicts in Wikipedia
In this work we study the dynamical features of editorial wars in Wikipedia
(WP). Based on our previously established algorithm, we build up samples of
controversial and peaceful articles and analyze the temporal characteristics of
the activity in these samples. On short time scales, we show that there is a
clear correspondence between conflict and burstiness of activity patterns, and
that memory effects play an important role in controversies. On long time
scales, we identify three distinct developmental patterns for the overall
behavior of the articles. We are able to distinguish cases eventually leading
to consensus from those cases where a compromise is far from achievable.
Finally, we analyze discussion networks and conclude that edit wars are mainly
fought by few editors only.Comment: Supporting information adde
Vandalism on Collaborative Web Communities: An Exploration of Editorial Behaviour in Wikipedia
Modern online discussion communities allow people to contribute, sometimes anonymously. Such flexibility sometimes threatens the reputation and reliability of community-owned resources. Such flexibility is understandable, however, they engender threats to the reputation and reliability in collective goods. Since not a lot of previous work addressed these issues it is important to study the aforementioned issues to build an innate understanding of recent ongoing vandalism of Wikipedia pages and ways to preventing those.
In this study, we consider the type of activity that the anonymous users carry out on Wikipedia and also contemplate how others react to their activities. In particular, we want to study vandalism of Wikipedia pages and ways of preventing this kind of activity. Our preliminary analysis reveals (~ 90%) of the vandalism or foul edits are done by unregistered users in Wikipedia due to nature of openness. The community reaction seemed to be immediate: most vandalisms were reverted within five minutes on an average. Further analysis shed light on the tolerance of Wikipedia community, reliability of anonymous users revisions and feasibility of early prediction of vandalism
Pushing Your Point of View: Behavioral Measures of Manipulation in Wikipedia
As a major source for information on virtually any topic, Wikipedia serves an
important role in public dissemination and consumption of knowledge. As a
result, it presents tremendous potential for people to promulgate their own
points of view; such efforts may be more subtle than typical vandalism. In this
paper, we introduce new behavioral metrics to quantify the level of controversy
associated with a particular user: a Controversy Score (C-Score) based on the
amount of attention the user focuses on controversial pages, and a Clustered
Controversy Score (CC-Score) that also takes into account topical clustering.
We show that both these measures are useful for identifying people who try to
"push" their points of view, by showing that they are good predictors of which
editors get blocked. The metrics can be used to triage potential POV pushers.
We apply this idea to a dataset of users who requested promotion to
administrator status and easily identify some editors who significantly changed
their behavior upon becoming administrators. At the same time, such behavior is
not rampant. Those who are promoted to administrator status tend to have more
stable behavior than comparable groups of prolific editors. This suggests that
the Adminship process works well, and that the Wikipedia community is not
overwhelmed by users who become administrators to promote their own points of
view
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