Content Analysis has been developed within communication science as a technique to analyze bodies of text for features or (recurring) themes, in order to identify cultural indicators, societal trends and issues. And while Content Analysis has seen a tremendous uptake across scientific disciplines, the advent of digital media has presented new challenges to the demarcation and study of content. Within Content Analysis, different strategies have been put forward to grapple with these dynamics. And although these approaches each present ways forward for the analysis of web content, they do not yet regard the vast differences between web platforms that serve content, which each have their own ‘technicities,’ e.g. carry their own (often visually undisclosed) formats and formatting, and output their own results and rankings. In this dissertation I therefore develop Networked Content Analysis as a term for such techniques of Content Analysis that are adapted specifically to the study of networked digital media content. The case in question is climate change, one of the major societal challenges of our times, which I study on the web and with search engines, on Wikipedia as well as Twitter. In all, my contribution provides footing for a return to the roots of Content Analysis and at the same time adds to its toolkit the necessary web- and platform-specific research techniques for creating a fine-grained picture of the climate change debate as it takes place across platforms.
|Award date||23 Jun 2016|
|Publication status||Published - 2016|