Wikipedia Research Research Articles

Wikipedia in the System of National Scientific Sovereignty: Literature Review

The object of the article is to review scientific articles, to evaluate Wikipedia in publications of native library science periodicals. Wikipedia is considered from the point of view of scientific activity management. The table is presented, which shows relative pros and cons of this electronic encyclopedia. Such disadvantages of this electronic resource as incomplete reflection of scientific subject areas, lack of professional categorization of electronic resources, influence from foreign copyright are noted, further direction of Wikipedia research in the system of national scientific sovereignty is determined as a subject-by-article analysis of the articles of this encyclopedia within the framework of certain scientific areas and, especially, in the field of library science and librarianship.

Two decades of Wikipedia research: a PubMed bibliometric network analysis

PurposeThis paper aims to examine the structure and dynamics of scholarly publications dealing with Wikipedia. The research also aims to investigate how such research evolved since its launch in 2001.Design/methodology/approachWikipedia has grown to be the biggest online encyclopedia in terms of comprehensiveness, reach and coverage. Based on 1,040 PubMed Wikipedia documents written by 5,280 authors over two decades (2001–2021), this paper conducts a bibliometric review of the intellectual structure of scholarly publications dealing with Wikipedia.FindingsResults show that annual scholarly publications on Wikipedia growth rate is 13.26. Major outlets publishing Wikipedia’s research are PloS One, the Journal of Medical Internet Research, Nucleic Acids Research, Studies in Health Technology and Informatics, Bioinformatics and the International Journal of Medical Informatics. Results also show that the author collaboration network is very sparse, signifying rather negligible collaboration among the authors. Furthermore, results reveal that the Wikipedia research institutions’ collaboration network reflects what is sometimes termed Wikipedia’s “North-South divide,” indicating limited collaboration between rich and poor nations’ institutions. Finally, the multiple correspondence analysis applied to obtain the Wikipedia research conceptual map and its intellectual structure reveals the intellectual thrust and the diversity of the scholarly publications dealing with Wikipedia.Originality/valueTo the best of the author’s knowledge, this research represents the first application of bibliometric methods to investigate two decades of scholarly publications dealing with Wikipedia based on the PubMed database.

Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks

We test the hypothesis that the extent to which one obtains information on a given topic through Wikipedia depends on the language in which it is consulted. Controlling the size factor, we investigate this hypothesis for a number of 25 subject areas. Since Wikipedia is a central part of the web-based information landscape, this indicates a language-related, linguistic bias. The article therefore deals with the question of whether Wikipedia exhibits this kind of linguistic relativity or not. From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading. For this purpose, it develops a hybrid model of intra- and intertextual similarity of different parts of the information landscape and tests this model on the example of 35 languages and corresponding Wikipedias. In this way the article builds a bridge between reading research, educational science, Wikipedia research and computational linguistics.

Using big data techniques for measuring productive friction in mass collaboration online environments

The advent of the social web brought with it challenges and opportunities for research on learning and knowledge construction. Using the online-encyclopedia Wikipedia as an example, we discuss several methods that can be applied to analyze the dynamic nature of knowledge-related processes in mass collaboration environments. These methods can help in the analysis of the interactions between the two levels that are relevant in computer-supported collaborative learning (CSCL) research: The individual level of learners and the collective level of the group or community. In line with constructivist theories of learning, we argue that the development of knowledge on both levels is triggered by productive friction, that is, the prolific resolution of socio-cognitive conflicts. By describing three prototypical methods that have been used in previous Wikipedia research, we review how these techniques can be used to examine the dynamics on both levels and analyze how these dynamics can be predicted by the amount of productive friction. We illustrate how these studies make use of text classifiers, social network analysis, and cluster analysis in order to operationalize the theoretical concepts. We conclude by discussing implications for the analysis of dynamic knowledge processes from a learning sciences perspective.

The_Tower_of_Babel.jpg: Diversity of Visual Encyclopedic Knowledge Across Wikipedia Language Editions

Across all Wikipedia language editions, millions of images augment text in critical ways. This visual encyclopedic knowledge is an important form of wikiwork for editors, a critical part of reader experience, an emerging resource for machine learning, and a lens into cultural differences. However, Wikipedia research--and cross-language edition Wikipedia research in particular--has thus far been limited to text. In this paper, we assess the diversity of visual encyclopedic knowledge across 25 language editions and compare our findings to those reported for textual content. Unlike text, translation in images is largely unnecessary. Additionally, the Wikimedia Foundation, through the Wikipedia Commons, has taken steps to simplify cross-language image sharing. While we may expect that these factors would reduce image diversity, we find that cross-language image diversity rivals, and often exceeds, that found in text. We find that diversity varies between language pairs and content types, but that many images are unique to different language editions. Our findings have implications for readers (in what imagery they see), for editors (in deciding what images to use), for researchers (who study cultural variations), and for machine learning developers (who use Wikipedia for training models).

Wikipedia and e-Collaboration Research

Wikipedia's precursor started in the year 2000 as a traditional online encyclopedia with content controlled by a small group of experts. In 2013 Wikipedia's current user-controlled incarnation was such a successful enterprise that an asteroid was named after it. The authors briefly discuss key opportunities and challenges in e-collaboration research on Wikipedia. The opportunities refer to studies on the impact of Wikipedia on individuals and organizations, as well as on the spontaneous formation of online communities. The main challenges discussed refer to the consensus-building nature of content creation in Wikipedia, making practical applications of findings somewhat limited, as well as data compilation difficulties.

Big data and Wikipedia research: social science knowledge across disciplinary divides

This paper examines research about Wikipedia that has been undertaken using big data approaches. The aim is to gauge the coherence as against the disparateness of studies from different disciplines, how these studies relate to each other, and to research about Wikipedia and new social media in general. The paper is partly based on interviews with big data researchers, and discusses a number of themes and implications of Wikipedia research, including about the workings of online collaboration, the way that contributions mirror (or not) aspects of real-world geographies, and how contributions can be used to predict offline social and economic trends. Among the findings is that in some areas of research, studies build on and extend each other's results. However, most of the studies stay within disciplinary silos and could be better integrated with other research on Wikipedia and with research about new media. Wikipedia is among few sources in big data research where the data are openly available, unlike many studies where data are proprietary. Thus, it has lent itself to a burgeoning and promising body of research. The paper concludes that in order to fulfil this promise, this research must pay more attention to theories and research from other disciplines, and also go beyond questions based narrowly on the availability of data and towards a more powerful analytical grasp of the phenomenon being investigated.

Wikipedia Research and Tools: Review and Comments

I here give an overview of Wikipedia and wiki research and tools. Well over 1,000 reports have been published in the eld and there exist dedicated scientic meetings for Wikipedia research. It is not possible to give a complete review of all material published. This overview serves to describe some key areas of research. i

The visibility of Wikipedia in scholarly publications

Publications in the Institute of Scientific Information’s (ISI, currently Thomson Reuters) Web of Science (WoS) and Elsevier’s Scopus databases were utilized to collect data about Wikipedia research and citations to Wikipedia. The growth of publications on Wikipedia research, the most active researchers, their associated institutions, academic fields and their geographic distribution are treated in this paper. The impact and influence of Wikipedia were identified, utilizing cited work found in (WoS) and Scopus. Additionally, leading authors, affiliated institutions, countries, academic fields, and publications that frequently cite Wikipedia are identified.

Analyzing the wikisphere: Methodology and data to support quantitative wiki research

AbstractOwing to the inherent difficulty in obtaining experimental data from wikis, past quantitative wiki research has largely focused on Wikipedia, limiting the ability to generalize such research. To facilitate the analysis of wikis other than Wikipedia, we developed WikiCrawler, a tool that automatically gathers research data from public wikis without supervision. We then built a corpus of 151 wikis, which we have made publicly available. Our analysis indicated that these wikis display signs of collaborative authorship, validating them as objects of study. We then performed an initial analysis of the corpus and discovered some similarities with Wikipedia, such as users contributing at unequal rates. We also analyzed distributions of edits across pages and users, resulting in data which can motivate or verify mathematical models of behavior on wikis. By providing data collection tools and a corpus of already‐collected data, we have completed an important first step for investigations that analyze user behavior, establish measurement baselines for wiki evaluation, and generalize Wikipedia research by testing hypotheses across many wikis.

Wikipedia & Research: The Innovative Character of Wikipedia Research and the New Challenges (and Opportunities) Associated With It.

The workshop will focus on addressing the stage of Wikipedia research and in general common - based peer production (less focused on the content than on the methodologies and research process itself) and the innovations, problems and new insights regarding (action) research on common-based peer production.

Analysing Geo-linguistic Dynamics of the World Wide Web: The Use of Cartograms and Network Analysis to Understand Linguistic Development in Wikipedia

Abstract This article discusses the usefulness of geo-linguistic analysis for Internet studies by presenting two techniques to frame and visualize the linguistic development of the World Wide Web, in particular the geo-linguistic development amongst different language versions of Wikipedia. An emergent research agenda has been set to explore the multilingual aspects of the Internet using, for example, a global perspective on Wikipedia research. And yet, there is a lack of theoretical and methodological tools for understanding the distribution and diffusion of linguistic materials online. The idea of geo-linguistic factors is introduced in this article to address these shortcomings and to respond to the study of a wide range of issues such as linguistic pluralism on the Internet or, more generally, the diffusion of innovation. Cartograms and network analysis are presented as two techniques that showcase the potential uses of geo-linguistic analysis. These two techniques of measurement and visualization indicate certain geographic and linguistic affiliations among languages. It is argued that although certain more developed language versions such as English and German may have central positions in connecting all languages, there exists another pattern that can best be explained by geo-linguistic factors. Finally, the limitations and implications of such findings and techniques are discussed, not only for research on Wikipedia but for Internet studies in general.

Global perspective on Wikipedia research

AbstractThis panel will provide a global perspective on Wikipedia research. The literature on Wikipedia is mostly anecdotal, and most of the research has focused attention primarily on the English Wikipedia examining the accuracy of entries compared to established online encyclopedias (Emigh & Herring, 2005; Giles, 2005; Rosenzweig, 2006) and analyzing the evolution of articles over time (Viégas, Wattenberg, & Dave, 2004; Viégas, Wattenberg, Kriss, & van Ham, 2007). Others have examined the quality of contribution (Stvilia et al., 2005). However, only a few studies have conducted comparative analyses across languages or analyzed Wikipedia in languages other than English (e.g., Pfeil, Zaphiris, & Ang, 2006). There is a need for international, cross‐cultural understanding of Wikipedia. In an effort to address this gap, this panel will present a range of international and cross‐cultural research of Wikipedia.The presenters will contribute different perspectives of Wikipedia as an international sociocultural institution and will describe similarities and differences across various national/language versions of Wikipedia. Shachaf and Hara will present variation of norms and behaviors on talk pages in various languages of Wikipedia. Herring and Callahan will share results from a cross‐language comparison of biographical entries that exhibit variations in content of entries in the English and Polish versions of Wikipedia and will explain how they are influenced by the culture and history of the US and Poland. Stvilia will discuss some of the commonalities and variability of quality models used by different Wikipedias, and the problems of cross‐language quality measurement aggregation and reasoning. Matei will describe the social structuration and distribution of roles and efforts in wiki teaching environments. Solomon's comments, as a discussant, will focus on how these comparative insights provide evidence of the ways in which an evolving institution, such as Wikipedia, may be a force for supporting cultural identity (or not).