Search (9 results, page 1 of 1)

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Abstract

Controversy is a complex concept that has been attracting attention of scholars from diverse fields. In the era of Internet and social media, detecting controversy and controversial concepts by the means of automatic methods is especially important. Web searchers could be alerted when the contents they consume are controversial or when they attempt to acquire information on disputed topics. Presenting users with the indications and explanations of the controversy should offer them chance to see the "wider picture" rather than letting them obtain one-sided views. In this work we first introduce a formal model of controversy as the basis of computational approaches to detecting controversial concepts. Then we propose a classification based method for automatic detection of controversial articles and categories in Wikipedia. Next, we demonstrate how to use the obtained results for the estimation of the controversy level of search queries. The proposed method can be incorporated into search engines as a component responsible for detection of queries related to controversial topics. The method is independent of the search engine's retrieval and search results recommendation algorithms, and is therefore unaffected by a possible filter bubble. Our approach can be also applied in Wikipedia or other knowledge bases for supporting the detection of controversy and content maintenance. Finally, we believe that our results could be useful for social science researchers for understanding the complex nature of controversy and in fostering their studies.

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Abstract

This study evaluates how well the authors of Wikipedia history articles adhere to the site's policy of assuring verifiability through citations. It does so by examining the references and citations of a subset of country histories. The findings paint a dismal picture. Not only are many claims not verified through citations, those that are suffer from the choice of references used. Many of these are from only a few US government Websites or news media and few are to academic journal material. Given these results, one response would be to declare Wikipedia unsuitable for serious reference work. But another option emerges when we jettison technological determinism and look at Wikipedia as a product of a wider social context. Key to this context is a world in which information is bottled up as commodities requiring payment for access. Equally important is the problematic assumption that texts are undifferentiated bearers of knowledge. Those involved in instructional programs can draw attention to the social nature of texts to counter these assumptions and by so doing create an awareness for a new generation of Wikipedians and Wikipedia users of the need to evaluate texts (and hence citations) in light of the social context of their production and use.

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Abstract

This study analyzes the search behavior of Dutch-speaking nursing students with a nonnative knowledge of English who searched for information in MEDLINE/PubMed about a specific theme in nursing. We examine whether and to what extent their search efficiency is affected by their language skills. Our task-oriented approach focuses on three stages of the information retrieval process: need articulation, query formulation, and relevance judgment. The test participants completed a pretest questionnaire, which gave us information about their overall experience with the search system and their self-reported computer and language skills. The students were briefly introduced to the use of PubMed and MeSH (medical subject headings) before they conducted their keyword-driven subject search. We assessed the search results in terms of recall and precision, and also analyzed the search process. After the search task, a satisfaction survey and a language test were completed. We conclude that language skills have an impact on the search results. We hypothesize that language support might improve the efficiency of searches conducted by Dutch-speaking users of PubMed.

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Abstract

Wikipedia is frequently viewed as an inclusive medium. But inclusivity within this online encyclopedia is not a simple matter of just allowing anyone to contribute. In its quest for legitimacy as an encyclopedia, Wikipedia relies on outsiders to judge claims championed by rival editors. In choosing these experts, Wikipedians define the boundaries of acceptable comment on any given subject. Inclusivity then becomes a matter of how the boundaries of expertise are drawn. In this article I examine the nature of these boundaries and the implications they have for inclusivity and credibility as revealed through the talk pages produced and sources used by a particular subset of Wikipedia's creators-those involved in writing articles on the topic of Philippine history.

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Abstract

Wikipedia, like other encyclopedias, includes biographies of notable people. However, because it is jointly written by many contributors, it is subject to constant manipulation by contributors attempting to add biographies of non-notable people. Over time, Wikipedia has developed inclusion criteria for notable people (e.g., receiving a significant award) based on which newly contributed biographies are evaluated. In this paper we present and analyze a set of simple indicators that can be used to predict which article will eventually be accepted. These indicators do not refer to the content itself, but to meta-content features (such as the number of categories that the biography is associated with) and to author-based features (such as if it is a first-time author). By training a classifier on these features, we successfully reached a high predictive performance (area under the receiver operating characteristic [ROC] curve [AUC] of 0.97) even though we overlooked the actual biography text.

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Abstract

Using the Arts & Humanities Citation Index (A&HCI) 2008, we apply mapping techniques previously developed for mapping journal structures in the Science and Social Sciences Citation Indices. Citation relations among the 110,718 records were aggregated at the level of 1,157 journals specific to the A&HCI, and the journal structures are questioned on whether a cognitive structure can be reconstructed and visualized. Both cosine-normalization (bottom up) and factor analysis (top down) suggest a division into approximately 12 subsets. The relations among these subsets are explored using various visualization techniques. However, we were not able to retrieve this structure using the Institute for Scientific Information Subject Categories, including the 25 categories that are specific to the A&HCI. We discuss options for validation such as against the categories of the Humanities Indicators of the American Academy of Arts and Sciences, the panel structure of the European Reference Index for the Humanities, and compare our results with the curriculum organization of the Humanities Section of the College of Letters and Sciences of the University of California at Los Angeles as an example of institutional organization.

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Date

1. 6.2010 10:13:22

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Date

18.11.2014 13:22:03

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Date

17. 2.2018 16:50:22