Revision history

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Revision history is included as keyword or extra keyword in 0 datasets, 1 tools and 13 publications.

Datasets

There is no datasets for this keyword.

Tools

Tool Operating System(s) Language(s) Programming language(s) License Description Image
MediaWiki Utilities Cross-platform English Python MIT license MediaWiki Utilities is a collection of utilities for working with XML data dumps generated for Wikimedia projects and other MediaWiki wikis.


Publications

Title Author(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Revision graph extraction in Wikipedia based on supergram decomposition and sliding update Wu J.
Mizuho Iwaihara
IEICE Transactions on Information and Systems English 2014 As one of the popular social media that many people turn to in recent years, collaborative encyclopedia Wikipedia provides information in a more "Neutral Point of View" way than others. Towards this core principle, plenty of efforts have been put into collaborative contribution and editing. The trajectories of how such collaboration appears by revisions are valuable for group dynamics and social media research, which suggest that we should extract the underlying derivation relationships among revisions from chronologically-sorted revision history in a precise way. In this paper, we propose a revision graph extraction method based on supergram decomposition in the document collection of near-duplicates. The plain text of revisions would be measured by its frequency distribution of supergram, which is the variable-length token sequence that keeps the same through revisions. We show that this method can effectively perform the task than existing methods. Copyright 0 0
Revision graph extraction in wikipedia based on supergram decomposition Wu J.
Mizuho Iwaihara
Proceedings of the 9th International Symposium on Open Collaboration, WikiSym + OpenSym 2013 English 2013 As one of the popular social media that many people turn to in recent years, collaborative encyclopedia Wikipedia provides information in a more "Neutral Point of View" way than others. Towards this core principle, plenty of efforts have been put into collaborative contribution and editing. The trajectories of how such collaboration appears by revisions are valuable for group dynamics and social media research, which suggest that we should extract the underlying derivation relationships among revisions from chronologically-sorted revision history in a precise way. In this paper, we propose a revision graph extraction method based on supergram decomposition in the document collection of near-duplicates. The plain text of revisions would be measured by its frequency distribution of supergram, which is the variable-length token sequence that keeps the same through revisions. We show that this method can effectively perform the task than existing methods. Categories and Subject Descriptors K.4.3 [Computers and Society]: Organizational Impacts - Computer-supported collaborative work. General Terms Algorithms, Experimentation. Copyright 2010 ACM. 0 0
A corpus-based study of edit categories in featured and non-featured wikipedia articles Daxenberger J.
Iryna Gurevych
24th International Conference on Computational Linguistics - Proceedings of COLING 2012: Technical Papers English 2012 In this paper, we present a study of the collaborative writing process in Wikipedia. Our work is based on a corpus of 1,995 edits obtained from 891 article revisions in the English Wikipedia. We propose a 21-category classification scheme for edits based on Faigley and Witte's (1981) model. Example edit categories include spelling error corrections and vandalism. In a manual multi-label annotation study with 3 annotators, we obtain an inter-annotator agreement of α = 0.67. We further analyze the distribution of edit categories for distinct stages in the revision history of 10 featured and 10 non-featured articles. Our results show that the information content in featured articles tends to become more stable after their promotion. On the opposite, this is not true for non-featured articles. We make the resulting corpus and the annotation guidelines freely available. 0 0
Visualizing author contribution statistics in Wikis using an edit significance metric Peter Kin-Fong Fong
Robert P. Biuk-Aghai
WikiSym English 2011 Wiki articles tend to be edited multiple times by multiple authors. This makes it difficult to identify individual authors’ contributions by human observation alone. We calculate an edit significance metric, using different weights for different types of edits, which reflect the different value placed on them by wiki community members. We then aggregate edit significance values and present them as visualizations to the user to aid in perceiving extent and patterns of contributions. 4 0
Wikipedia revision toolkit: efficiently accessing Wikipedia's edit history Oliver Ferschke
Torsten Zesch
Iryna Gurevych
HLT English 2011 0 0
What Did They Do? Deriving High-Level Edit Histories in Wikis Peter Kin-Fong Fong
Robert P. Biuk-Aghai
WikiSym English 2010 Wikis have become a popular online collaboration platform. Their open nature can, and indeed does, lead to a large number of editors of their articles, who create a large number of revisions. These editors make various types of edits on an article, from minor ones such as spelling correction and text formatting, to major revisions such as new content introduction, whole article re-structuring, etc. Given the enormous number of revisions, it is difficult to identify the type of contributions made in these revisions through human observation alone. Moreover, different types of edits imply different edit significance. A revision that introduces new content is arguably more significant than a revision making a few spelling corrections. By taking edit types into account, better measurements of edit significance can be produced. This paper proposes a method for categorizing and presenting edits in an intuitive way and with a flexible measure of significance of each individual editor’s contributions. 11 2
What did they do? Deriving high-level edit histories in wikis Fong P.K.-F.
Biuk-Aghai R.P.
WikiSym 2010 English 2010 Wikis have become a popular online collaboration platform. Their open nature can, and indeed does, lead to a large number of editors of their articles, who create a large number of revisions. These editors make various types of edits on an article, from minor ones such as spelling correction and text formatting, to major revisions such as new content introduction, whole article re-structuring, etc. Given the enormous number of revisions, it is difficult to identify the type of contributions made in these revisions through human observation alone. Moreover, different types of edits imply different edit significance. A revision that introduces new content is arguably more significant than a revision making a few spelling corrections. By taking edit types into account, better measurements of edit significance can be produced. This paper proposes a method for categorizing and presenting edits in an intuitive way and with a flexible measure of significance of each individual editor's contributions. 0 2
Organizing the vision for web 2.0: A study of the evolution of the concept in Wikipedia Arnaud Gorgeon
Swanson E.B.
WikiSym English 2009 Information Systems (IS) innovations are often characterized by buzzwords, reflecting organizing visions that structure and express the images and ideas formed by a wide community of users about their meaning and purpose. In this paper, we examine the evolution of Web 2.0, a buzzword that is now part of the discourse of a broad community, and look at its entry in Wikipedia over the three years since its inception in March 2005. We imported the revision history from Wikipedia, and analyzed and categorized the edits that were performed and the users that contributed to the article. The patterns of evolution of the types and numbers of contributors and edits lead us to propose four major periods in the evolution of the Web 2.0 article: Seeding, Germination, Growth and Maturity. During the Seeding period, the article evolved mostly underground, with few edits and few contributors active. The article growth took off during the Germination period, receiving increasing attention. Growth was the most active period of development, but also the most controversial. During the last period, Maturity, the article received a decreasing level of attention, current and potential contributors losing interest, as a consensus about what the concept of Web 2.0 means seemed to have been reached. Copyright 0 2
Organizing the vision for web 2.0: a study of the evolution of the concept in Wikipedia Arnaud Gorgeon
E. Burton Swanson
WikiSym English 2009 0 2
Automated Building of Error Corpora of Polish Marcin Milkowski Corpus Linguistics, Computer Tools, and Applications – State of the Art. PALC 2007, Peter Lang. Internationaler Verlag der Wissenschaften 2008, 631-639 2008 The paper shows how to automatically develop error corpora out of revision history of documents. The idea is based on a hypothesis that minor edits in documents represent correction of typos, slips of the tongue, grammar, usage and style mistakes. This hypothesis has been confirmed by frequency analysis of revision history of articles in the Polish Wikipedia. Resources such as revision history in Wikipedia, Wikia, and other collaborative editing systems, can be turned into corpora of errors, just by extracting the minor edits. The most theoretically interesting aspect is that the corrections will represent the average speaker's intuitions about usage, and this seems to be a promising way of researching normativity in claims about proper or improper Polish. By processing the revision history, one can gain pairs of segments in the corpus: first representing the error, and the other representing the correction. Moreover, it is relatively easy to tag parts of speech, compare subsequent versions, and prepare a text file containing the resulting corpus. 0 0
Mining Wikipedia's Article Revision History for Training Computational Linguistics Algorithms Rani Nelken
Elif Yamangil
WikiAI English 2008 0 0
Structuring Wiki Revision History Mikalai Sabel WikiSym English 2007 Revision history of a wiki page is traditionally maintained as a linear chronological sequence. We propose to represent revision history as a tree of versions. Every edge in the tree is given a weight, called adoption coefficient, indicating similarity between the two corresponding page versions. The same coefficients are used to build the tree. In the implementation described, adoption coefficients are derived from comparing texts of the versions, similarly to computing edit distance. The tree structure reflects actual evolution of page content, revealing reverts, vandalism, and edit wars, which is demonstrated on Wikipedia examples. The tree representation is useful for both human editors and automated algorithms, including trust and reputation schemes for wiki. 0 1
Studying cooperation and conflict between authors with history flow visualizations Fernanda B. Viégas
Martin Wattenberg
Kushal Dave
Conference on Human Factors in Computing Systems English 2004 The Internet has fostered an unconventional and powerful style of collaboration: “wiki” web sites, where every visitor has the power to become an editor. In this paper we investigate the dynamics of Wikipedia, a prominent, thriving wiki. We make three contributions. First, we introduce a new exploratory data analysis tool, the history flow visualization, which is effective in revealing patterns within the wiki context and which we believe will be useful in other collaborative situations as well. Second, we discuss several collaboration patterns highlighted by this visualization tool and corroborate them with statistical analysis. Third, we discuss the implications of these patterns for the design and governance of online collaborative social spaces. We focus on the relevance of authorship, the value of community surveillance in ameliorating antisocial behavior, and how authors with competing perspectives negotiate their differences. 3 23