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

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.