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On the Interpretation of Digital Trace Data in Communication and Social Computing Research

机译:通信与社会计算研究中数字跟踪数据的解释

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The widespread availability of analytical tools for Big Data offers enormous opportunities and challenges for communication researchers. In contrast to user-generated texts, digital trace data (evidence of online user activities such as hyperlinks and retweets) represent a new methodological frontier for the field. However, interpretive strategies remain scattered and ad hoc with few best practices to guide them. To help remedy this situation, this article reviews recent scholarship in both communication and social computing research that has incorporated three common types of trace data: hyperlinks, Twitter followers, and retweets. It finds that while researchers in both fields have interpreted each trace in a variety of ways, they have largely declined to explain the validity of their interpretations.
机译:大数据分析工具的广泛使用为通信研究人员提供了巨大的机遇和挑战。与用户生成的文本相比,数字跟踪数据(在线用户活动的证据,例如超链接和转发)代表了该领域的新方法论前沿。但是,解释策略仍然是零散的并且是临时性的,几乎没有最佳实践来指导它们。为了帮助纠正这种情况,本文回顾了通信和社交计算研究领域的最新研究成果,该研究结合了三种常见的跟踪数据类型:超链接,Twitter关注者和转发。研究发现,尽管两个领域的研究人员都以各种方式解释了每种痕迹,但他们很大程度上拒绝解释其解释的有效性。

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