Ecology in the digital world of Wikipedia (original) (raw)

Ecology of the digital world of Wikipedia

Scientific Reports

Wikipedia, a paradigmatic example of online knowledge space is organized in a collaborative, bottom-up way with voluntary contributions, yet it maintains a level of reliability comparable to that of traditional encyclopedias. The lack of selected professional writers and editors makes the judgement about quality and trustworthiness of the articles a real challenge. Here we show that a self-consistent metrics for the network defined by the edit records captures well the character of editors’ activity and the articles’ level of complexity. Using our metrics, one can better identify the human-labeled high-quality articles, e.g., “featured” ones, and differentiate them from the popular and controversial articles. Furthermore, the dynamics of the editor-article system is also well captured by the metrics, revealing the evolutionary pathways of articles and diverse roles of editors. We demonstrate that the collective effort of the editors indeed drives to the direction of article improvem...

Cooperation and quality in wikipedia

Proceedings of the 2007 international symposium on Wikis - WikiSym '07, 2007

The rise of the Internet has enabled collaboration and cooperation on an unprecedentedly large scale. The online encyclopedia Wikipedia, which presently comprises 7.2 million articles created by 7.04 million distinct editors, provides a consummate example. We examined all 50 million edits made to the 1.5 million English-language Wikipedia articles and found that the high-quality articles are distinguished by a marked increase in number of edits, number of editors, and intensity of cooperative behavior, as compared to other articles of similar visibility and age. This is significant because in other domains, fruitful cooperation has proven to be difficult to sustain as the size of the collaboration increases. Furthermore, in spite of the vagaries of human behavior, we show that Wikipedia articles accrete edits according to a simple stochastic mechanism in which edits beget edits. Topics of high interest or relevance are thus naturally brought to the forefront of quality.

Measuring Article Quality in Wikipedia using the Collaboration Network

Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015, 2015

Collaboratively edited articles such as in Wikipedia suffer from well-identified problems regarding their quality, e.g., information accuracy, reputability of third-party sources, vandalism. Due to the huge number of articles and the intensive edit rate, the manual evaluation of article content quality is inconceivable. In this paper, we tackle the problem of automatically establishing the quality of Wikipedia articles. Evidences are shown to consider the interactions between authors and articles to assess the quality score. Collaborations between authors and reviewers are also considered to reinforce the discriminative process. This work gives a generic formulation of the Mutual Reinforcement principle held between articles quality and authors authority and take explicitly advantage of the co-edits graph generated by individuals. Experiments conducted on a set of representative data from Wikipedia show the effectiveness of our approach.

Analyzing the Creative Editing Behavior of Wikipedia Editors

Procedia - Social and Behavioral Sciences, 2010

This paper analyzes editing patterns of Wikipedia contributors using dynamic social network analysis. We have developed a tool that converts the edit flow among contributors into a temporal social network. We are using this approach to identify the most creative Wikipedia editors among the few thousand contributors who make most of the edits amid the millions of active Wikipedia editors. In particular, we identify the key category of "coolfarmers", the prolific authors starting and building new articles of high quality. Towards this goal we analyzed the 2580 featured articles of the English Wikipedia where we found two main article types: (1) articles of narrow focus created by a few subject matter experts, and (2) articles about a broad topic created by thousands of interested incidental editors. We then investigated the authoring process of articles about a current and controversial event. There we found two types of editors with different editing patterns: the mediators, trying to reconcile the different viewpoints of editors, and the zealots, who are adding fuel to heated discussions on controversial topics. As a second category of editors we look at the "egoboosters", people who use Wikipedia mostly to showcase themselves. Understanding these different patterns of behavior gives important insights about the cultural norms of online creators. In addition, identifying and policing egoboosters has the potential to increase the quality of Wikipedia. People best suited to enforce culture-compliant behavior of egoboosters through exemplary behavior and active intervention are the highly regarded coolfarmers introduced above.

Assessing the Quality of Wikipedia Pages Using Edit Longevity and Contributor Centrality

2012

Abstract: In this paper we address the challenge of assessing the quality of Wikipedia pages using scores derived from edit contribution and contributor authoritativeness measures. The hypothesis is that pages with significant contributions from authoritative contributors are likely to be high-quality pages. Contributions are quantified using edit longevity measures and contributor authoritativeness is scored using centrality metrics in either the Wikipedia talk or co-author networks.

Statistical Measure of the Effectiveness of the Open Editing Model of Wikipedia

2010

Wikipedia is commonly viewed as the main online encyclopedia. Its content quality, however, has often been questioned due to the open nature of its editing model. A highquality contribution by an expert may be followed by a lowquality contribution made by an amateur or vandal; therefore the quality of each article may fluctuate over time as it goes through iterations of edits by different users. In this study, we model the evolution of content quality in Wikipedia articles in order to estimate the fraction of time during which articles retain high-quality status. The results show that articles tend to have high-quality content 74% of their lifetime and the average article quality increases as articles go through edits. To further analyze the open editing model of Wikipedia, we compare the behaviour of anonymous and registered users and show that there is a positive correlation between registration and quality of the contributed content. In addition, we compare the evolution of the content in Wikipedia known high-quality articles (aka. featured articles) and the rest of the articles in order to extract features affecting quality. The results show that the high turnover of the content caused by the open editing model of Wikipedia results in rapid elimination of low-quality content.These results not only suggest that the process underlying Wikipedia can be used for producing high-quality content, but also to question the viability of collaborative knowledge repositories that impose high barriers to user participation for the purpose of filtering poor quality contributions from the onset.

Assessing the value of cooperation in Wikipedia

First Monday, 2007

Since its inception six years ago, the online encyclopedia Wikipedia has accumulated 6.40 million articles and 250 million edits, contributed in a predominantly undirected and haphazard fashion by 5.77 million unvetted volunteers. Despite the apparent lack of order, the 50 million edits by 4.8 million contributors to the 1.5 million articles in the English-language Wikipedia follow strong certain overall regularities. We show that the accretion of edits to an article is described by a simple stochastic mechanism, resulting in a heavy tail of highly visible articles with a large number of edits. We also demonstrate a crucial correlation between article quality and number of edits, which validates Wikipedia as a successful collaborative effort.

A Characterization of Wikipedia Content Based on Motifs in the Edit Graph

2011

Abstract Wikipedia works because of the many eyes idea. Good Wikipedia pages are authoritative sources because a number of knowledgeable contributors have collaborated to produce an authoritative article on a topic. In this paper we explore the hypothesis that the extent to which the many eyes idea is true for a specific article can be assessed by looking at the edit graph associated with that article, ie the network of contributors and articles.

Co-authorship 2.0 : Patterns of collaboration in Wikipedia

The study of collaboration patterns in wikis can help shed light on the process of content creation by online communities. To turn a wiki's revision history into a collaboration network, we propose an algorithm that identifies as authors of a page the users who provided the most of its relevant content, measured in terms of quantity and of acceptance by the community. The scalability of this approach allows us to study the English Wikipedia community as a co-authorship network. We find evidence of the presence of a nucleus of very active contributors, who seem to spread over the whole wiki, and to interact preferentially with inexperienced users. The fundamental role played by this elite is witnessed by the growing centrality of sociometric stars in the network. Isolating the community active around a category, it is possible to study its specific dynamics and most influential authors.

Measuring article quality in wikipedia

Proceedings of the sixteenth ACM conference on Conference on information and knowledge management - CIKM '07, 2007

Wikipedia has grown to be the world largest and busiest free encyclopedia, in which articles are collaboratively written and maintained by volunteers online. Despite its success as a means of knowledge sharing and collaboration, the public has never stopped criticizing the quality of Wikipedia articles edited by non-experts and inexperienced contributors. In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia. We propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history. Our Basic model is designed based on the mutual dependency between article quality and their author authority. The PeerReview model introduces the review behavior into measuring article quality. Finally, our ProbReview models extend PeerReview with partial reviewership of contributors as they edit various portions of the articles. We conduct experiments on a set of well-labeled Wikipedia articles to evaluate the effectiveness of our quality measurement models in resembling human judgement.