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Social Media Analyses for Social Measurement

机译:社交媒体进行社会衡量分析

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摘要

Demonstrations that analyses of social media content can align with measurement from sample surveys have raised the question of whether survey research can be supplemented or even replaced with less costly and burdensome data mining of already-existing or “found” social media content. But just how trustworthy such measurement can be—say, to replace official statistics—is unknown. Survey researchers and data scientists approach key questions from starting assumptions and analytic traditions that differ on, for example, the need for representative samples drawn from frames that fully cover the population. New conversations between these scholarly communities are needed to understand the potential points of alignment and non-alignment. Across these approaches, there are major differences in (a) how participants (survey respondents and social media posters) understand the activity they are engaged in; (b) the nature of the data produced by survey responses and social media posts, and the inferences that are legitimate given the data; and (c) practical and ethical considerations surrounding the use of the data. Estimates are likely to align to differing degrees depending on the research topic and the populations under consideration, the particular features of the surveys and social media sites involved, and the analytic techniques for extracting opinions and experiences from social media. Traditional population coverage may not be required for social media content to effectively predict social phenomena to the extent that social media content distills or summarizes broader conversations that are also measured by surveys.
机译:社交媒体内容的分析可以与抽样调查的测量结果相吻合的演示提出了一个问题,即是否可以用成本更低,负担更重的现有或“发现”社交媒体内容的数据挖掘来补充或取代调查研究。但是,如何衡量这种衡量标准(例如代替官方统计数据)的可信度还未知。调查研究人员和数据科学家从不同的假设和分析传统出发,来解决关键问题,例如,需要从完全覆盖人群的框架中抽取代表性样本。这些学术团体之间需要进行新的对话,以了解结盟和不结盟的潜在要点。在这些方法之间,存在以下主要差异:(a)参与者(调查受访者和社交媒体海报)如何理解他们所从事的活动; (b)调查答复和社交媒体帖子所产生的数据的性质,以及根据这些数据得出的合理推论; (c)围绕数据使用的实践和道德考虑。估计值可能会根据研究主题和所考虑的人群,所涉及的调查和社交媒体站点的特定功能以及从社交媒体中提取意见和经验的分析技术而在不同程度上进行调整。社交媒体内容可以有效地预测社交现象,社交媒体内容可以提炼或总结也由调查衡量的更广泛的对话,因此可能不需要传统的人口覆盖范围。

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