This page compiles all the information regarding Netherlands.
EventsThis is a list of events celebrated in this country.
|Name||Type||DateThis property is a special property in this wiki.||Website|
|Wiki Loves Monuments 2010||contest||September 2010|
|Wikipedia CPOV Conference 2010 Amsterdam||conference||26 March 2010|
AuthorsThis is a list of authors in this country.
PublicationsThis is a list of publications by authors of this country.
|Title||Author(s)||Keyword(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Factual accuracy and trust in information: The role of expertise||Teun Lucassen
Jan Maarten Schraagen
|Journal of the American Society for Information Science and Technology||English||July 2011||In the past few decades, the task of judging the credibility of information has shifted from trained professionals (e.g., editors) to end users of information (e.g., casual Internet users). Lacking training in this task, it is highly relevant to research the behavior of these end users. In this article, we propose a new model of trust in information, in which trust judgments are dependent on three user characteristics: source experience, domain expertise, and information skills. Applying any of these three characteristics leads to different features of the information being used in trust judgments; namely source, semantic, and surface features (hence, the name 3S-model). An online experiment was performed to validate the 3S-model. In this experiment, Wikipedia articles of varying accuracy (semantic feature) were presented to Internet users. Trust judgments of domain experts on these articles were largely influenced by accuracy whereas trust judgments of novices remained mostly unchanged. Moreover, despite the influence of accuracy, the percentage of trusting participants, both experts and novices, was high in all conditions. Along with the rationales provided for such trust judgments, the outcome of the experiment largely supports the 3S-model, which can serve as a framework for future research on trust in information.||0||0|
|Evaluating WikiTrust: A trust support tool for Wikipedia||Teun Lucassen
Jan Maarten Schraagen
|First Monday||English||May 2011||Because of the open character of Wikipedia readers should always be aware of the possibility of false information. WikiTrust aims at helping readers to judge the trustworthiness of articles by coloring the background of less trustworthy words in a shade of orange. In this study we look into the effects of such coloring on reading behavior and trust evaluation by means of an eye–tracking experiment. The results show that readers had more difficulties reading the articles with coloring than without coloring. Trust in heavily colored articles was lower. The main concern is that the participants in our experiment rated usefulness of WikiTrust low.||7||0|
|Experiences with Semantic Wikis for Architectural Knowledge Management||Remco C. de Boer
Hans van Vliet
|Architectural knowledge management
|WICSA||English||2011||In this paper, we reflect on our experiences with using semantic wikis for architectural knowledge management in two different contexts: e-government and distributed software development. Whereas our applications of semantic wikis in e-government focus on organizing and structuring architectural knowledge for reuse, the applications in distributed software development focus on searching and querying architectural knowledge. Yet, the emerging research challenges - alignment of knowledge models, knowledge versioning, change acknowledgements - are very similar.||0||0|
|Need to categorize: A comparative look at the categories of the Universal Decimal Classification system (UDC) and Wikipedia||Almila Akdag Salah
|English||2011||This study analyzes the differences between the category structure of the Universal Decimal Classification (UDC) system (which is one of the widely used library classification systems in Europe) and Wikipedia. In particular, we compare the emerging structure of category-links to the structure of classes in the UDC. With this comparison we would like to scrutinize the question of how do knowledge maps of the same domain differ when they are created socially (i.e. Wikipedia) as opposed to when they are created formally (UDC) using classification theory. As a case study, we focus on the category of "Arts".||3||0|
|Reference Blindness: The Influence of References on Trust in Wikipedia||Teun Lucassen
Matthijs L. Noordzij
Jan Maarten Schraagen
|WebSci Conference||English||2011||In this study we show the influence of references on trust in information. We changed the contents of reference lists of Wikipedia articles in such a way that the new references were no longer in any sense related to the topic of the article. Furthermore, the length of the reference list was varied. College students were asked to evaluate the credibility of these articles. Only 6 out of 23 students noticed the manipulation of the references; 9 out of 23 students noticed the variations in length. These numbers are remarkably low, as 17 students indicated they considered references an important indicator of credibility. The findings suggest a highly heuristic manner of credibility evaluation. Systematic evaluation behavior was also observed in the experiment, but only of participants with low trust in Wikipedia in general.||7||0|
|Trust in Wikipedia: how users trust information from an unknown source||Teun Lucassen
Jan M. Schraagen
|English||2010||The use of Wikipedia as an information source is becoming increasingly popular. Several studies have shown that its information quality is high. Normally, when considering information trust, the source of information is an important factor. However, because of the open-source nature of Wikipedia articles, their sources remain mostly unknown. This means that other features need to be used to assess the trustworthiness of the articles. We describe article features - such as images and references - which lay Wikipedia readers use to estimate trustworthiness. The quality and the topics of the articles are manipulated in an experiment to reproduce the varying quality on Wikipedia and the familiarity of the readers with the topics. We show that the three most important features are textual features, references and images.||0||2|