“The Sum of All Human Knowledge”: A Systematic Review of Scholarly Research on the Content of Wikipedia

Wikipedia might possibly be the best-developed attempt thus far of the enduring quest to gather all human knowledge in one place. Its accomplishments in this regard have made it an irresistible point of inquiry for researchers from various fields of knowledge. A decade of research has thrown light on many aspects of the Wikipedia community, its processes, and content. However, due to the variety of the fields inquiring about Wikipedia and the limited synthesis of the extensive research, there is little consensus on many aspects of Wikipedia’s content as an encyclopedic collection of human knowledge. This study addresses the issue by systematically reviewing 110 peer-reviewed publications on Wikipedia content, summarizing the current findings, and highlighting the major research trends. Two major streams of research are identified: the quality of Wikipedia content (including comprehensiveness, currency, readability and reliability) and the size of Wikipedia. Moreover, we present the key research trends in terms of the domains of inquiry, research design, data source, and data gathering methods. This review synthesizes scholarly understanding of Wikipedia content and paves the way for future studies

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

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.Comment: 40 pages, 13 figures, 5 table

“The sum of all human knowledge”: A systematic review of scholarly research on the content of Wikipedia

Wikipedia might possibly be the best-developed attempt thus far of the enduring quest to gather all human knowledge in one place. Its accomplishments in this regard have made it an irresistible point of inquiry for researchers from various fields of knowledge. A decade of research has thrown light on many aspects of the Wikipedia community, its processes, and content. However, due to the variety of the fields inquiring about Wikipedia and the limited synthesis of the extensive research, there is little consensus on many aspects of Wikipedia’s content as an encyclopedic collection of human knowledge. This study addresses the issue by systematically reviewing 110 peer-reviewed publications on Wikipedia content, summarizing the current findings, and highlighting the major research trends. Two major streams of research are identified: the quality of Wikipedia content (including comprehensiveness, currency, readability and reliability) and the size of Wikipedia. Moreover, we present the key research trends in terms of the domains of inquiry, research design, data source, and data gathering methods. This review synthesizes scholarly understanding of Wikipedia content and paves the way for future studies

Classifying Bias in Large Multilingual Corpora via Crowdsourcing and Topic Modeling

Our project extends previous algorithmic approaches to finding bias in large text corpora. We used multilingual topic modeling to examine language-specific bias in the English, Spanish, and Russian versions of Wikipedia. In particular, we placed Spanish articles discussing the Cold War on a Russian-English viewpoint spectrum based on similarity in topic distribution. We then crowdsourced human annotations of Spanish Wikipedia articles for comparison to the topic model. Our hypothesis was that human annotators and topic modeling algorithms would provide correlated results for bias. However, that was not the case. Our annotators indicated that humans were more perceptive of sentiment in article text than topic distribution, which suggests that our classifier provides a different perspective on a text’s bias

“The sum of all human knowledge”: A systematic review of scholarly research on the content of Wikipedia

Wikipedia might possibly be the best-developed attempt thus far of the enduring quest to gather all human knowledge in one place. Its accomplishments in this regard have made it an irresistible point of inquiry for researchers from various fields of knowledge. A decade of research has thrown light on many aspects of the Wikipedia community, its processes, and content. However, due to the variety of the fields inquiring about Wikipedia and the limited synthesis of the extensive research, there is little consensus on many aspects of Wikipedia’s content as an encyclopedic collection of human knowledge. This study addresses the issue by systematically reviewing 110 peer-reviewed publications on Wikipedia content, summarizing the current findings, and highlighting the major research trends. Two major streams of research are identified: the quality of Wikipedia content (including comprehensiveness, currency, readability and reliability) and the size of Wikipedia. Moreover, we present the key research trends in terms of the domains of inquiry, research design, data source, and data gathering methods. This review synthesizes scholarly understanding of Wikipedia content and paves the way for future studies

Dynamics of disagreement: large-scale temporal network analysis reveals negative interactions in online collaboration

Disagreement and conflict are a fact of social life. However, negative interactions are rarely explicitly declared and recorded and this makes them hard for scientists to study. In an attempt to understand the structural and temporal features of negative interactions in the community, we use complex network methods to analyze patterns in the timing and configuration of reverts of article edits to Wikipedia. We investigate how often and how fast pairs of reverts occur compared to a null model in order to control for patterns that are natural to the content production or are due to the internal rules of Wikipedia. Our results suggest that Wikipedia editors systematically revert the same person, revert back their reverter, and come to defend a reverted editor. We further relate these interactions to the status of the involved editors. Even though the individual reverts might not necessarily be negative social interactions, our analysis points to the existence of certain patterns of negative social dynamics within the community of editors. Some of these patterns have not been previously explored and carry implications for the knowledge collection practice conducted on Wikipedia. Our method can be applied to other large-scale temporal collaboration networks to identify the existence of negative social interactions and other social processes

Multi-lingual and multi-cultural information literacy; perspectives, models and good practice

Purpose This paper reviews current approaches to, and good practice, in information literacy development in multi-lingual and multi-cultural settings, with particular emphasis on provision for international students. Design/methodology/approach A selective and critical review of published literature is extended by evaluation of examples of multi-lingual information literacy tutorials and MOOCs. Findings Multi-lingual and multi-cultural information literacy are umbrella terms covering a variety of situations and issues. This provision is of increasing importance in an increasingly mobile and multi-cultural world. This article evaluates current approaches and good practice, focusing on issues of culture vis a vis language, the balance between individual and group needs, specific and generic information literacy instruction, and models for information literacy, pedagogy and culture. Recommendations for good practice and for further research are given, Originality/value This is one of very few articles critically reviewing how information literacy development is affected by linguistic and cultural factors