PublicationsOnly those publications related to wikis already available at WikiPapers are shown here.
|Title||Author(s)||Keyword(s)||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Content Volatility of Scientific Topics in Wikipedia: A Cautionary Tale||Adam M. Wilson
Gene E. Likens
|English||14 August 2015||Wikipedia has quickly become one of the most frequently accessed encyclopedic references, despite the ease with which content can be changed and the potential for ‘edit wars’ surrounding controversial topics. Little is known about how this potential for controversy affects the accuracy and stability of information on scientific topics, especially those with associated political controversy. Here we present an analysis of the Wikipedia edit histories for seven scientific articles and show that topics we consider politically but not scientifically “controversial” (such as evolution and global warming) experience more frequent edits with more words changed per day than pages we consider “noncontroversial” (such as the standard model in physics or heliocentrism). For example, over the period we analyzed, the global warming page was edited on average (geometric mean ±SD) 1.9±2.7 times resulting in 110.9±10.3 words changed per day, while the standard model in physics was only edited 0.2±1.4 times resulting in 9.4±5.0 words changed per day. The high rate of change observed in these pages makes it difficult for experts to monitor accuracy and contribute time-consuming corrections, to the possible detriment of scientific accuracy. As our society turns to Wikipedia as a primary source of scientific information, it is vital we read it critically and with the understanding that the content is dynamic and vulnerable to vandalism and other shenanigans. (cc-by)||0||0|
|Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data||Márton Mestyán
|English||2013||Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.||0||0|
|Education in Health Research Methodology: Use of a Wiki for Knowledge Translation||Hamm M.P.
|English||2013||Introduction:A research-practice gap exists between what is known about conducting methodologically rigorous randomized controlled trials (RCTs) and what is done. Evidence consistently shows that pediatric RCTs are susceptible to high risk of bias; therefore novel methods of influencing the design and conduct of trials are required. The objective of this study was to develop and pilot test a wiki designed to educate pediatric trialists and trainees in the principles involved in minimizing risk of bias in RCTs. The focus was on preliminary usability testing of the wiki.Methods:The wiki was developed through adaptation of existing knowledge translation strategies and through tailoring the site to the identified needs of the end-users. The wiki was evaluated for usability and user preferences regarding the content and formatting. Semi-structured interviews were conducted with 15 trialists and systematic reviewers, representing varying levels of experience with risk of bias or the conduct of trials. Data were analyzed using content analysis.Results:Participants found the wiki to be well organized, easy to use, and straightforward to navigate. Suggestions for improvement tended to focus on clarification of the text or on esthetics, rather than on the content or format. Participants liked the additional features of the site that were supplementary to the text, such as the interactive examples, and the components that focused on practical applications, adding relevance to the theory presented. While the site could be used by both trialists and systematic reviewers, the lack of a clearly defined target audience caused some confusion among participants.Conclusions:Participants were supportive of using a wiki as a novel educational tool. The results of this pilot test will be used to refine the risk of bias wiki, which holds promise as a knowledge translation intervention for education in medical research methodology.||0||0|
|Dynamics of Conflicts in Wikipedia||Taha Yasseri
|English||June 2012||In this work we study the dynamical features of editorial wars in Wikipedia (WP). Based on our previously established algorithm, we build up samples of controversial and peaceful articles and analyze the temporal characteristics of the activity in these samples. On short time scales, we show that there is a clear correspondence between conflict and burstiness of activity patterns, and that memory effects play an important role in controversies. On long time scales, we identify three distinct developmental patterns for the overall behavior of the articles. We are able to distinguish cases eventually leading to consensus from those cases where a compromise is far from achievable. Finally, we analyze discussion networks and conclude that edit wars are mainly fought by few editors only.||44||1|
|Circadian patterns of Wikipedia editorial activity: A demographic analysis||Taha Yasseri
|English||2012||Wikipedia (WP) as a collaborative, dynamical system of humans is an appropriate subject of social studies. Each single action of the members of this society, i.e. editors, is well recorded and accessible. Using the cumulative data of 34 Wikipedias in different languages, we try to characterize and find the universalities and differences in temporal activity patterns of editors. Based on this data, we estimate the geographical distribution of editors for each WP in the globe. Furthermore we also clarify the differences among different groups of WPs, which originate in the variance of cultural and social features of the communities of editors.||10||2|
|Wiki-Pi: A Web-Server of Annotated Human Protein-Protein Interactions to Aid in Discovery of Protein Function||Orii N.
|English||2012||Protein-protein interactions (PPIs) are the basis of biological functions. Knowledge of the interactions of a protein can help understand its molecular function and its association with different biological processes and pathways. Several publicly available databases provide comprehensive information about individual proteins, such as their sequence, structure, and function. There also exist databases that are built exclusively to provide PPIs by curating them from published literature. The information provided in these web resources is protein-centric, and not PPI-centric. The PPIs are typically provided as lists of interactions of a given gene with links to interacting partners; they do not present a comprehensive view of the nature of both the proteins involved in the interactions. A web database that allows search and retrieval based on biomedical characteristics of PPIs is lacking, and is needed. We present Wiki-Pi (read Wiki-π), a web-based interface to a database of human PPIs, which allows users to retrieve interactions by their biomedical attributes such as their association to diseases, pathways, drugs and biological functions. Each retrieved PPI is shown with annotations of both of the participant proteins side-by-side, creating a basis to hypothesize the biological function facilitated by the interaction. Conceptually, it is a search engine for PPIs analogous to PubMed for scientific literature. Its usefulness in generating novel scientific hypotheses is demonstrated through the study of IGSF21, a little-known gene that was recently identified to be associated with diabetic retinopathy. Using Wiki-Pi, we infer that its association to diabetic retinopathy may be mediated through its interactions with the genes HSPB1, KRAS, TMSB4X and DGKD, and that it may be involved in cellular response to external stimuli, cytoskeletal organization and regulation of molecular activity. The website also provides a wiki-like capability allowing users to describe or discuss an interaction. Wiki-Pi is available publicly and freely at http://severus.dbmi.pitt.edu/wiki-pi/.||0||0|