This study discusses how the online encyclopedia, Wikipedia, which adopts an open source model, affects its readers¡¦ trust and related behaviors. The open editing format that every internet users can be an editor on the Wikipeidia arouse contiguous criticism for the knowledge accuracy and authority. The purpose of this research is to study the attitudes and usage intention of general Internet users for an online encyclopedia such as Wikipedia. We integrate trust, technology acceptance model (TAM), and content rating as the theory framework. It is of interest to approach why people would adopt Wikipedia as a knowledge resource and how they trust in it. In addition, we add the content rating as a moderator in the research model in order to verify whether the rating system on the Wikipedia would enhance trust or usage intention for readers. This study proposes a quasi-experiment with college students as the subjects. Those students have to complete a task before they answer a questionnaire that is to reflect their attitudes and usage intention for the Wikipedia. After the statistic analysis and research discussion, we are able to verify the proposed theory framework and provide the interpretation for the results. The results show that there are relationships between trust and TAM. Among the constructs, the Perceved Usefulness has more direct influence toward use intention. This appears people would consider the Perceved Usefulness for first important element judging for adopting Wikipedia or not. The content rating of Wikipedia would effectively moderate the relatonships between trust and use intention. When the content rating situation exists, readers of Wikipedia would increase their intention through trust of Wikipedia. For the managerial implication, the research findings can provide a reason why internet users trust the web site and how they will use it. The web site designers or operators should emphasize on enhancing features that would improve its accountability and credibility.

No description available.

This study investigated differences in R-PAS variables among two groups of participants, those who studied a Wikipedia article with information about the Rorschach (N=44) and those who did not (N=42). This study utilized a repeated measures design, wherein all of the participants took the Rorschach twice. The first time all participants completed the Rorschach under normal conditions. The second time all participants completed the Rorschach under the fake good condition, meaning they were motivated to present themselves in a favorable light. Participants in the experimental group were instructed to read the Wikipedia material before taking the test and to use this information to help them fake good. Results indicated that after reading the Wikipedia material, participants' responses demonstrated significantly improved perceptual accuracy (lower FQ-%). However, the overall findings suggested that most of the selected R-PAS variables were not significantly impacted by exposure to the Wikipedia material. All participants had changes in scores on a number of variables when asked to fake good, regardless of whether or not they were exposed to the Wikipedia material. Results indicated that when participants attempted to fake good, they were able to significantly improve markers of affect regulation (lower CF+C/SumC), coping effectiveness (higher MC-PPD), and interpersonal competency (lower PHR/GPHR). They were also likely to give less complex responses (lower Complexity) that were fewer in total number (lower R). Implications of these results and recommendations for forensic practice are discussed. / text

No description available.

The purpose of this thesis is to explore the following research question: Are there grammatical textual differences between Encyclopedia Britannica and Wikipedia? Specifically, this study will focus on the articles for "Communism" and "Dwight D. Eisenhower" that appear in the online version of Encyclopedia Britannica and Wikipedia. Using a grammatical textual analysis, the study finds there is little difference grammatically between Encyclopedia Britannica and Wikipedia though they are very different types of systems. There are several different types of textual or contextual methods that could expand on this initial approach to find differences between Encyclopedia Britannica and Wikipedia. / Department of Telecommunications

Zugl.: Osnabrück, Univ., Diplomarbeit, 2006

Wikipedia is the product of thousands of editors working collaboratively to provide free and up-to-date encyclopedic information to the project's users. This article asks to what degree Wikipedia articles in three languages — Hindi, Urdu, and English — achieve Wikipedia's mission of making neutrally-presented, reliable information on a polarizing, controversial topic available to people around the globe. We chose the topic of the recent revocation of Article 370 of the Constitution of India, which, along with other recent events in and concerning the region of Jammu and Kashmir, has drawn attention to related articles on Wikipedia. This work focuses on the English Wikipedia, being the preeminent language edition of the project, as well as the Hindi and Urdu editions. Hindi and Urdu are the two standardized varieties of Hindustani, a lingua franca of Jammu and Kashmir. We analyzed page view and revision data for three Wikipedia articles to gauge popularity of the pages in our corpus, and responsiveness of editors to breaking news events and problematic edits. Additionally, we interviewed editors from all three language editions to learn about differences in editing processes and motivations, and we compared the text of the articles across languages as they appeared shortly after the revocation of Article 370. Across languages,we saw discrepancies in article tone, organization, and the information presented, as well as differences in how editors collaborate and communicate with one another. Nevertheless, in Hindi and Urdu, as well as English, editors predominantly try to adhere to the principle of neutral point of view (NPOV), and for the most part, the editors quash attempts by other editors to push political agendas. / Master of Science / Wikipedia aims to have articles fairly represent controversial topics. It's especially important that articles are updated quickly and malicious edits are caught as events warrant. In smaller language editions of the project, it's a challenge to keep articles both current and "neutral."We chose five articles related to the ongoing conflict in Jammu and Kashmir and compared them across three language editions of Wikipedia: English (often seen as the gold standard of the project, having been around the longest and having by far the most contributors of any language edition), Hindi, and Urdu. Hindi and Urdu are the two standardized varieties of Hindustani; both are widely spoken in and around Jammu and Kashmir, but particularly, Urdu is the national language of Pakistan and Hindi is most widely spoken in Northern India. With some exceptions, we found that across language editions, editors were quick to respond to breaking news events and problematic edits, and they strove to uphold Wikipedia's core tenet of neutral point of view (NPOV).

No description available.

The free online encyclopedia Wikipedia is one of the most successful collaborative web projects. It is based on an open editing model, which allows everyone to edit the articles directly in the web browser. As a result of the open concept undesirable contributions like vandalism cannot be ruled out. These contributions reduce the article quality temporarily, consume system resources and cause effort for correcting. To address these problems, this paper introduces an approach for automatic editing rights management in Wikipedia that assigns editing rights according to the reputation of the author and the quality of the article to be edited. This analysis shows that this approach reduces undesirable contributions significantly while valuable contributions are nearly unaffected.

Data provenance refers to the lineage or pedigree of data, including information such as its origin and key events that affect it over the course of its lifecycle. In recent years, provenance has become increasingly important as more and more people are using data that they themselves did not generate. Tracking data provenance helps ensure that data provided by many different providers and sources can be trusted and used appropriately. Data provenance also has several other critical uses, including data quality assessment, generating data replication recipes, data security management, etc.One of the major objectives of our research is to investigate the semantics or meaning of data provenance. We describe a generic ontology of data provenance called the W7 model that represents the semantics of data provenance. Formalized in the conceptual graph formalism, the W7 model represents provenance as a combination of seven interconnected elements including "what," "when," "where," "how," "who," "which" and "why." The W7 model is designed to be general and comprehensive enough to cover a broad range of provenance-related vocabularies. However, the W7 model alone, no matter how comprehensive it is, is insufficient for capturing all domain-specific provenance requirements. We hence present a novel approach to developing domain ontologies of provenance. This approach relies on various conceptual graph mechanisms, including schema definitions and canonical formation rules, and enables us to easily adapt and extend the W7 model to develop domain ontologies of provenance. The W7 model for data provenance has been widely adopted and adapted for use within Raytheon Missile Systems and the iPlant Collaborative, as well as the US Army's ATRAP IV (Asymmetric Threat Response and Analysis Program) system.We also developed a domain ontology of provenance for Wikipedia based on the W7 model. This domain ontology enables us to extract provenance for each Wikipedia article. We present a study in which we use their provenance to assess the quality of Wikipedia articles. Assessing and guaranteeing data quality has become a critical concern that, to a large extent, determines the future success and survival of Wikipedia since the quality of Wikipedia has been continuously called into question due to various incidents of vandalism and misinformation since its launch in 2001. Our study shows that the quality of Wikipedia articles depends not only on the different types of contributors but also on how they collaborate. We identify a number of contributor roles based on the provenance. Based on the roles and provenance, our research identifies several collaboration patterns that are preferable or detrimental for data quality, thus providing insights for designing tools and mechanisms to improve Wikipedia article quality.