Making sense of self-reported socially significant data using computational methods
Making sense of self-reported socially significant data using computational methods
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DOI：
10.1080/13645579.2013.774174
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发表时间：
2013-05-01
影响因子：
3.3
通讯作者：
Rana, Omer F.
中科院分区：
文献类型：
--
作者：
Burnap, Peter;Avis, Nick J.;Rana, Omer F.
越来越多的人使用社交媒体与同龄人交流并记录个人日常感受和观点，这正在创造出规模巨大的数据，这为社会科学家提供了进行社会互动的民族志、话语和内容分析等研究的机会，从而为当今社会提供了额外的见解。然而，进行此类分析所需的工具和方法通常是孤立的和/或专有的。卡迪夫在线社交媒体观测站 (COSMOS) 提供了一个集成的虚拟研究环境，用于支持社交媒体数据的收集、分析和可视化，为研究人员提供了一种创新设施，可以在其上进行假设性实验，从而得出可靠的结果。本研究提出了数字社会研究的方法，并解释了 COSMOS 的功能如何支持该方法。
The growing number of people using social media to communicate with their peers and document their personal everyday feelings and views is creating a data on an epic scale' that provides the opportunity for social scientists to conduct research such as ethnography, discourse and content analysis of social interactions, providing an additional insight into today's society. However, the tools and methods required to conduct such analysis are often isolated and/or proprietary. The Cardiff Online Social Media Observatory (COSMOS) provides an integrated virtual research environment for supporting the collection, analysis, and visualization of social media data, providing researchers with an innovative facility on which to conduct hypothetical experiments that lead to defensible results. This study presents a methodology for Digital Social Research and explains how the features of COSMOS aim to underpin it.