From Data Analytics to Data Hermeneutics. Online Political Discussions, Digital Methods and the Continuing Relevance of Interpretive Approaches
From Data Analytics to Data Hermeneutics. Online Political Discussions, Digital Methods and the Continuing Relevance of Interpretive Approaches
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从数据分析到数据解释学。
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发表时间：
2016
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通讯作者：
P. Gerbaudo
中科院分区：
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作者：
P. Gerbaudo
摘要为了推进数字政治的研究，迫切需要用数据解释学来补充数据分析，将其理解为一种方法论方法，专注于解释社交媒体对话中意义的深层结构，因为它们围绕从数字抗议运动到在线竞选活动的各种政治现象而发展。大数据技术在最近的政治行为学术中的传播，导致了对网络政治现象的理解存在数量上的偏差，忽视了内容和意义的问题。为了解决这一问题，有必要使解释学方法适应社交媒体传播的条件，并将其分析对象从文本转移到数据集。一方面，这涉及确定从数据集中挑选社交媒体帖子样本的程序，以便对它们进行更深入的分析。我描述了三种抽样策略-顶层抽样、随机抽样和放大抽样-以实现这一目标。另一方面，解释学分析中使用的“近距离阅读”程序需要适应数字对象与传统文本不同的质量。这可以通过分析帖子不仅作为数据集中的数据点，而且作为集体对话中的干预，以及作为更广泛的“话语”的发言来实现。解释社交媒体数据的任务还需要了解数字政治现象展开的政治和社会背景，并考虑到参与者的主观观点和动机，这些观点和动机可以通过深入访谈和其他定性社会科学方法获得。因此，数据解释学有望缩小数字政治研究中定量和定性方法之间的差距，使人们能够更深入、更全面地理解在线政治现象。
Abstract To advance the study of digital politics it is urgent to complement data analytics with data hermeneutics to be understood as a methodological approach that focuses on the interpretation of the deep structures of meaning in social media conversations as they develop around various political phenomena, from digital protest movements to online election campaigns. The diffusion of Big Data techniques in recent scholarship on political behavior has led to a quantitative bias in the understanding of online political phenomena and a disregard for issues of content and meaning. To solve this problem it is necessary to adapt the hermeneutic approach to the conditions of social media communication, and shift its object of analysis from texts to datasets. On the one hand, this involves identifying procedures to select samples of social media posts out of datasets, so that they can be analysed in more depth. I describe three sampling strategies - top sampling, random sampling and zoom-in sampling - to attain this goal. On the other hand, “close reading” procedures used in hermeneutic analysis need to be adapted to the different quality of digital objects vis-à-vis traditional texts. This can be achieved by analysing posts not only as data-points in a dataset, but also as interventions in a collective conversation, and as utterances of broader “discourses”. The task of interpretation of social media data also requires an understanding of the political and social contexts in which digital political phenomena unfold, as well as taking into account the subjective viewpoints and motivations of those involved, which can be gained through in-depth interviews, and other qualitative social science methods. Data hermeneutics thus holds promise for a closing of the gap between quantitative and qualitative approaches in the study of digital politics, allowing for a deeper and more holistic understanding of online political phenomena.