نتایج جستجو برای: Vandalism

تعداد نتایج: 520  

2015
Khoi-Nguyen Dao Tran Thao Tran

Vandalism, the malicious modification or editing of articles, is a serious problem for free and open access online encyclopedias such as Wikipedia. Over the 13 year lifetime of Wikipedia, editors have identified and repaired vandalism in 1.6% of more than 500 million revisions of over 9 million English articles, but smaller manually inspected sets of revisions for research show vandalism may ap...

2011
Manoj Harpalani Michael Hart Sandesh Signh Rob Johnson Yejin Choi

Community-based knowledge forums, such as Wikipedia, are susceptible to vandalism, i.e., ill-intentioned contributions that are detrimental to the quality of collective intelligence. Most previous work to date relies on shallow lexico-syntactic patterns and metadata to automatically detect vandalism in Wikipedia. In this paper, we explore more linguistically motivated approaches to vandalism de...

Journal: :Adolescence 1988
C Tygart

Public school vandalism was investigated with a sample of students in 7th through 12th grade. Vandalism was found to be the highest in Grade 7 and decreased progressively with each increase in grade level. Being from classes in the lowest academic track was the strongest predictor of school vandalism. For high school students, having committed acts of vandalism during their junior high year was...

Journal: :CoRR 2010
Santiago Moisés Mola-Velasco

Wikipedia is an online encyclopedia that anyone can edit. In this open model, some people edits with the intent of harming the integrity of Wikipedia. This is known as vandalism. We extend the framework presented in (Potthast, Stein, and Gerling, 2008) for Wikipedia vandalism detection. In this approach, several vandalism indicating features are extracted from edits in a vandalism corpus and ar...

2011
Si-Chi Chin William Nick Street

This paper adopts an unsupervised subclass discovery approach to automatically improve the taxonomy of Wikipedia vandalism. Wikipedia vandalism, defined as malicious editing intended to compromise the integrity of the content of articles, exhibits heterogeneous characteristics, making it hard to detect automatically. The categorization of vandalism provides insights on the detection of vandalis...

Journal: :CoRR 2014
Andrea Ballatore

This article addresses the emergent phenomenon of carto-vandalism, the intentional defacement of collaborative cartographic digital artefacts in the context of volunteered geographic information. Through a qualitative analysis of reported incidents in WikiMapia and OpenStreetMap, a typology of this kind of vandalism is outlined, including play, ideological, fantasy, artistic, and industrial car...

Journal: :ISPRS Int. J. Geo-Information 2012
Pascal Neis Marcus Götz Alexander Zipf

The OpenStreetMap (OSM) project, a well-known source of freely available worldwide geodata collected by volunteers, has experienced a consistent increase in popularity in recent years. One of the main caveats that is closely related to this popularity increase is different types of vandalism that occur in the projects database. Since the applicability and reliability of crowd-sourced geodata, a...

2015
Khoi-Nguyen Tran Peter Christen Scott Sanner Lexing Xie

The malicious modification of articles, termed vandalism, is a serious problem for open access encyclopedias such as Wikipedia. Wikipedia’s counter-vandalism bots and past vandalism detection research have greatly reduced the exposure and damage of common and obvious types of vandalism. However, there remains increasingly more sneaky types of vandalism that are clearly out of context of the sen...

2010
Santiago M. Mola Velasco

Wikipedia is an online encyclopedia that anyone can edit. In this open model, some people edits with the intent of harming the integrity of Wikipedia. This is known as vandalism. We extend the framework presented in (Potthast, Stein, and Gerling, 2008) for Wikipedia vandalism detection. In this approach, several vandalism indicating features are extracted from edits in a vandalism corpus and ar...

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