Qualidade de artigos na wikipedia para seus usuários - análise e proposta de interação

AUTOR(ES)
FONTE

IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia

DATA DE PUBLICAÇÃO

25/03/2011

RESUMO

Wikipedia has drawn much attention from scientists because of its bold proposal to create an open, collaborative encyclopedia, and even more for being so popular. Since the creation of Wikipedia in 2001 by Jimbo Wales and Larry Sanger, its growth hás been dizzying surpassing 2.5 million articles in English version. However, the use of such content faces the challenge of ensuring the reliability of information. Even though Wikipedia had been compared to Encyclopedia Britannica, it faces the following risks: accuracy, motivation, expertise, stability, coverage and sources as points the work of Denning et al. [2005]. Given this scenario, this work has as main objective to propose a computational system called GreenWiki quality indicators to assist users of wikis, like Wikipedia, to review an article based on predefined quality criteria. Unlike many efforts in the field, this work does not intend to automatically select which article is good or bad. The user is, ultimately, responsible for evaluating the information provided by the tool and deciding what level of confidence she/he has in the content presented. As first step of this work, an inspection of Wikipedia interface was conducted in order to identify and evaluate strategies that it uses to communicates to users aspects regarding the quality of articles [Santos &Prates, 2010]. For the inspection, we used the Semiotic Inspection Method (SIM) [de Souza et al., 2006; de Souza &Leitão, 2009; de Souza et al., 2010; Prates &Barbosa, 2007] based on Semiotic Engineering theory. Besides developing GreenWiki, we also evaluated the prototype through interviews with nine participants using the Underlying Discourse Unveiling Method (UDUM) [Nicolaci-da Costa et al., 2004]. With these interviews, we analyze the impact of using GreenWiki in assessing the quality of the content available on Wikipedia. Our results showed that, using techniques of visualization and textual explanations, it is possible to inform users about the status of articles and help them in their task of evaluating the articles.

ASSUNTO(S)

computação teses. interação homem-maquina teses. interfaces de usuário (sistema de computador) teses. sistemas de recuperação da informação semiótica teses.

ACESSO AO ARTIGO

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