Qualitative analysis

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qualitative analysis is included as keyword or extra keyword in 0 datasets, 0 tools and 6 publications.


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Title Author(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Maturity assessment of Wikipedia medical articles Conti R.
Marzini E.
Spognardi A.
Matteucci I.
Mori P.
Petrocchi M.
Proceedings - IEEE Symposium on Computer-Based Medical Systems English 2014 Recent studies report that Internet users are growingly looking for health information through the Wikipedia Medicine Portal, a collaboratively edited multitude of articles with contents often comparable with professionally edited material. Automatic quality assessment of the Wikipedia medical articles has not received much attention by Academia and it presents open distinctive challenges. In this paper, we propose to tag the medical articles on the Wikipedia Medicine Portal, clearly stating their maturity degree, intended as a summarizing measure of several article properties. For this purpose, we adopt the Analytic Hierarchy Process, a well known methodology for decision making, and we evaluate the maturity degree of more than 24000 Wikipedia medical articles. The obtained results show how the qualitative analysis of medical content not always overlap with a quantitative analysis (an example of which is shown in the paper), since important properties of an article can hardly be synthesized by quantitative features. This seems particularly true when the analysis considers the concept of maturity, defined and verified in this work. 0 0
Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia Jessica J. Neff
David Laniado
Karolin E. Kappler
Yana Volkovich
Pablo Aragón
Andreas Kaltenbrunner
PLOS ONE English 3 April 2013 Background

In their 2005 study, Adamic and Glance coined the memorable phrase ‘divided they blog’, referring to a trend of cyberbalkanization in the political blogosphere, with liberal and conservative blogs tending to link to other blogs with a similar political slant, and not to one another. As political discussion and activity increasingly moves online, the power of framing political discourses is shifting from mass media to social media.

Methodology/Principal Findings

Continued examination of political interactions online is critical, and we extend this line of research by examining the activities of political users within the Wikipedia community. First, we examined how users in Wikipedia choose to display their political affiliation. Next, we analyzed the patterns of cross-party interaction and community participation among those users proclaiming a political affiliation. In contrast to previous analyses of other social media, we did not find strong trends indicating a preference to interact with members of the same political party within the Wikipedia community.


Our results indicate that users who proclaim their political affiliation within the community tend to proclaim their identity as a ‘Wikipedian’ even more loudly. It seems that the shared identity of ‘being Wikipedian’ may be strong enough to triumph over other potentially divisive facets of personal identity, such as political affiliation.
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Cultural bias in Wikipedia content on famous persons Ewa S. Callahan
Susan C. Herring
Journal of the American Society for Information Science and Technology English 2011 Wikipedia advocates a strict "neutral point of view" (NPOV) policy. However, although originally a U.S-based, English-language phenomenon, the online, user-created encyclopedia now has versions in many languages. This study examines the extent to which content and perspectives vary across cultures by comparing articles about famous persons in the Polish and English editions of Wikipedia. The results of quantitative and qualitative content analyses reveal systematic differences related to the different cultures, histories, and values of Poland and the United States; at the same time, a U.S./English-language advantage is evident throughout. In conclusion, the implications of these findings for the quality and objectivity of Wikipedia as a global repository of knowledge are discussed, and recommendations are advanced for Wikipedia end users and content developers. 22 2
Mentoring in Wikipedia: A clash of cultures Musicant D.R.
Yingjie Ren
Johnson J.A.
John Riedl
WikiSym 2011 Conference Proceedings - 7th Annual International Symposium on Wikis and Open Collaboration English 2011 The continuous success of Wikipedia depends upon its capability to recruit and engage new editors, especially those with new knowledge and perspectives. Yet Wikipedia over the years has become a complicated bureaucracy that may be difficult for newcomers to navigate. Mentoring is a practice that has been widely used in offline organizations to help new members adjust to their roles. In this paper, we draw insights from the offline mentoring literature to analyze mentoring practices in Wikipedia and how they influence editor behaviors. Our quantitative analysis of the Adopt-a-user program shows mixed success of the program. Communication between adopters and adoptees is correlated with the amount of article editing done by adoptees shortly after adoption. Our qualitative analysis of the communication between adopters and adoptees suggests that several key functions of mentoring are missing or not fulfilled consistently. Most adopters focus on establishing their legitimacy rather than acting proactively to guide, protect, and support the long-term growth of adoptees. We conclude with recommendations of how Wikipedia mentoring programs can evolve to take advantage of offline best practices. 0 2
A qualitative analysis of sub-degree students commentary styles and patterns in the context of gender and peer e-feedback Leung K.
Chan M.
Maxwell G.
Poon T.
Lecture Notes in Computer Science English 2010 While research interest is building in the role and effectiveness of electronic based peer feedback (Peer e-Feedback) in the context of L1/L2 English writing, that of Chinese language education at sub-degree level has been neglected. This paper seeks to address this shortfall by examining aspects of how sub-degree level students at a Hong Kong Community College respond to peer roles in the context of e-feedback to written work in a Wiki-supported Chinese language class. The work focuses on identifying the predominant commentary styles employed in a Wiki-supported peer-reviewed writing environment (WPWE) and also gives attention to the question of Gender to probe features and scope, similarities and differences displayed between female and male students. Among the patterns identified was the trend to produce feedback in a descending order, viz: (1) offering a solution; (2) identification of a problem/good point; (3) explanation; (4) localization; and (5) elaboration. Some gender differences emerged e.g. males tended to offer 'specific suggestions' more readily than female students. Interestingly and importantly, both genders demonstrated inabilities and or reluctance to offer requests for elaboration - evidence that some well designed training may be desired before conducting online peer-reviewed writing activity. It was evident too, that positive feedback outnumbered negative feedback even when some helpful corrective criticism was clearly needed and appropriate. Overall, the many positives far outweighed some negatives in the educational value of Peer e-feedback as a useful tool in Chinese language education. The study also showed that there is a need to further refine and clearly define some of the terminology now appearing in this important area of research. 0 0
Automatically suggesting topics for augmenting text documents Robert West
Doina Precup
Joelle Pineau
International Conference on Information and Knowledge Management, Proceedings English 2010 We present a method for automated topic suggestion. Given a plain-text input document, our algorithm produces a ranking of novel topics that could enrich the input document in a meaningful way. It can thus be used to assist human authors, who often fail to identify important topics relevant to the context of the documents they are writing. Our approach marries two algorithms originally designed for linking documents to Wikipedia articles, proposed by Milne and Witten [15] and West et al. [22], While neither of them can suggest novel topics by itself, their combination does have this capability. The key step towards finding missing topics consists in generalizing from a large background corpus using principal component analysis. In a quantitative evaluation we conclude that our method achieves the precision of human editors when input documents are Wikipedia articles, and we complement this result with a qualitative analysis showing that the approach also works well on other types of input documents. 0 0