19,214 research outputs found
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
Modeling the Wikipedia to Understand the Dynamics of Long Disputes and Biased Articles
The Internet has provided us with a number of online collaborative environments, including platforms for open software developments and online encyclopedias such as Wikipedia. Conflicts may arise in the course of such collaboration, but despite differences of opinion consensus can be reached. By investigating the consensus-building processes, we can shed light on the dynamics of social behavior. In Wikipedia, it is not always easy for editors to agree about article content, especially considering people’s different tolerance levels towards others and for whatever may be written. In this paper, we focus on how the editors' attitudes, namely being broad-minded or stubborn, affect the consensus-building process in a model of Wikipedia. We further investigate how banning editors affects the speed with which conflicts or debates can be resolved. For the analysis, we use an agent-based opinion model developed to simulate different aspects of Wikipedia. We show that, in most cases, banning agents from editing an article slows down the consensus-building process, and increases the system’s relaxation time. We show further, and counterintuitively, that with large groups of “extremists” who hold other than the central opinion, consensus can be reached faster and the article will be less biased
Opinions, Conflicts and Consensus: Modeling Social Dynamics in a Collaborative Environment
Information-communication technology promotes collaborative environments like
Wikipedia where, however, controversiality and conflicts can appear. To
describe the rise, persistence, and resolution of such conflicts we devise an
extended opinion dynamics model where agents with different opinions perform a
single task to make a consensual product. As a function of the convergence
parameter describing the influence of the product on the agents, the model
shows spontaneous symmetry breaking of the final consensus opinion represented
by the medium. In the case when agents are replaced with new ones at a certain
rate, a transition from mainly consensus to a perpetual conflict occurs, which
is in qualitative agreement with the scenarios observed in Wikipedia.Comment: 6 pages, 5 figures. Submitted for publicatio
The most controversial topics in Wikipedia: A multilingual and geographical analysis
We present, visualize and analyse the similarities and differences between
the controversial topics related to "edit wars" identified in 10 different
language versions of Wikipedia. After a brief review of the related work we
describe the methods developed to locate, measure, and categorize the
controversial topics in the different languages. Visualizations of the degree
of overlap between the top 100 lists of most controversial articles in
different languages and the content related to geographical locations will be
presented. We discuss what the presented analysis and visualizations can tell
us about the multicultural aspects of Wikipedia and practices of
peer-production. Our results indicate that Wikipedia is more than just an
encyclopaedia; it is also a window into convergent and divergent social-spatial
priorities, interests and preferences.Comment: This is a draft of a book chapter to be published in 2014 by
Scarecrow Press. Please cite as: Yasseri T., Spoerri A., Graham M., and
Kert\'esz J., The most controversial topics in Wikipedia: A multilingual and
geographical analysis. In: Fichman P., Hara N., editors, Global
Wikipedia:International and cross-cultural issues in online collaboration.
Scarecrow Press (2014
Circadian patterns of Wikipedia editorial activity: A demographic analysis
Wikipedia (WP) as a collaborative, dynamical system of humans is an
appropriate subject of social studies. Each single action of the members of
this society, i.e. editors, is well recorded and accessible. Using the
cumulative data of 34 Wikipedias in different languages, we try to characterize
and find the universalities and differences in temporal activity patterns of
editors. Based on this data, we estimate the geographical distribution of
editors for each WP in the globe. Furthermore we also clarify the differences
among different groups of WPs, which originate in the variance of cultural and
social features of the communities of editors
A Graph-structured Dataset for Wikipedia Research
Wikipedia is a rich and invaluable source of information. Its central place
on the Web makes it a particularly interesting object of study for scientists.
Researchers from different domains used various complex datasets related to
Wikipedia to study language, social behavior, knowledge organization, and
network theory. While being a scientific treasure, the large size of the
dataset hinders pre-processing and may be a challenging obstacle for potential
new studies. This issue is particularly acute in scientific domains where
researchers may not be technically and data processing savvy. On one hand, the
size of Wikipedia dumps is large. It makes the parsing and extraction of
relevant information cumbersome. On the other hand, the API is straightforward
to use but restricted to a relatively small number of requests. The middle
ground is at the mesoscopic scale when researchers need a subset of Wikipedia
ranging from thousands to hundreds of thousands of pages but there exists no
efficient solution at this scale.
In this work, we propose an efficient data structure to make requests and
access subnetworks of Wikipedia pages and categories. We provide convenient
tools for accessing and filtering viewership statistics or "pagecounts" of
Wikipedia web pages. The dataset organization leverages principles of graph
databases that allows rapid and intuitive access to subgraphs of Wikipedia
articles and categories. The dataset and deployment guidelines are available on
the LTS2 website \url{https://lts2.epfl.ch/Datasets/Wikipedia/}
Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data
Use of socially generated "big data" to access information about collective
states of the minds in human societies has become a new paradigm in the
emerging field of computational social science. A natural application of this
would be the prediction of the society's reaction to a new product in the sense
of popularity and adoption rate. However, bridging the gap between "real time
monitoring" and "early predicting" remains a big challenge. Here we report on
an endeavor to build a minimalistic predictive model for the financial success
of movies based on collective activity data of online users. We show that the
popularity of a movie can be predicted much before its release by measuring and
analyzing the activity level of editors and viewers of the corresponding entry
to the movie in Wikipedia, the well-known online encyclopedia.Comment: 13 pages, Including Supporting Information, 7 Figures, Download the
dataset from: http://wwm.phy.bme.hu/SupplementaryDataS1.zi
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