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

机译:大数据和维基百科研究:跨学科分歧的社会科学知识

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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.
机译:本文考察了使用大数据方法进行的有关维基百科的研究。目的是衡量不同学科研究之间的一致性,这些研究之间的关系,以及对维基百科和新的社交媒体的总体研究。本文部分基于对大数据研究人员的采访,并讨论了Wikipedia研究的许多主题和含义,包括有关在线协作的工作,贡献反映(或不反映)现实世界各个方面的方式以及如何贡献可用于预测离线的社会和经济趋势。这些发现是,在某些研究领域中,研究是建立在彼此的结果之上并相互扩展的。但是,大多数研究都处于学科孤岛内,可以更好地与Wikipedia上的其他研究以及有关新媒体的研究相结合。 Wikipedia是大数据研究中可公开获取数据的少数资源之一,与许多数据专有的研究不同。因此,它已成为新兴和有前途的研究机构。本文的结论是,为了实现这一诺言,这项研究必须更多地关注其他学科的理论和研究,并且不仅限于基于数据可用性的问题,而且还应更有效地分析所研究的现象。

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