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Conceptual frameworks for social and cultural Big Data analytics: Answering the epistemological challenge

机译:社会和文化大数据分析的概念框架:回答认识论挑战

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This paper aims to contribute to the development of tools to support an analysis of Big Data as manifestations of social processes and human behaviour. Such a task demands both an understanding of the epistemological challenge posed by the Big Data phenomenon and a critical assessment of the offers and promises coming from the area of Big Data analytics. This paper draws upon the critical social and data scientists’ view on Big Data as an epistemological challenge that stems not only from the sheer volume of digital data but, predominantly, from the proliferation of the narrow-technological and the positivist views on data. Adoption of the social-scientific epistemological stance presupposes that digital data was conceptualised as manifestations of the social. In order to answer the epistemological challenge, social scientists need to extend the repertoire of social scientific theories and conceptual frameworks that may inform the analysis of the social in the age of Big Data. However, an ‘epistemological revolution’ discourse on Big Data may hinder the integration of the social scientific knowledge into the Big Data analytics.
机译:本文旨在为支持大数据分析,作为社会流程和人类行为的表现,有助于开发工具。这样的任务要求了解大数据现象所带来的认识论挑战,以及对来自大数据分析领域的优惠和承诺的关键评估。本文借鉴了大量数据和数据科学家认为大数据的观点,作为源于数字数据的庞大数量,而且主要是从狭义技术和实证主义的数据的扩散来源于狭义上的认识论挑战。通过社会科学认识论立场的推出假定数字数据被视为社会表现的概念化。为了回答认识论挑战,社会科学家需要扩展社会科学理论和概念框架的曲目,这些框架可能会通知社会在大数据时代的分析。然而,关于大数据的“认识论革命”话语可能会阻碍社会科学知识的整合到大数据分析中。

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