Abstract
User comments in response to newspaper articles published online offer a unique resource for studying online discourse. The number of comments that articles often elicit poses many methodological challenges and analyses of online user comments have inevitably been cursory when limited to a manual content or thematic analysis. Corpus analysis tools can systematically identify features such as keywords in large datasets. This article reports on the semantic annotation feature of the corpus analysis tool WMatrix which also allows us to identify key semantic domains. Building on this feature, I introduce a novel method of sampling key comments through an examination of user comment threads taken from The Guardian website on the topic of climate change.
Highlights
The user comments section that follows articles published by journalists online is one format of discussion that is publicly accessible and very popular in the U.K
Previous research looking at online user comments has generally been based on manual content analysis and as such has been limited in the scope with which it can represent online debates (Manosevitch and Walker 2009; Milioni et al 2012; Coe et al 2014)
The identification of key categories through semantic annotation incorporated more of the detail of the data than basic keyword analysis
Summary
The user comments section that follows articles published by journalists online is one format of discussion that is publicly accessible and very popular in the U.K. Previous research looking at online user comments has generally been based on manual content analysis and as such has been limited in the scope with which it can represent online debates (Manosevitch and Walker 2009; Milioni et al 2012; Coe et al 2014). Such content analysis requires a very close reading of the data in order to construct a coding framework which is very demanding, given the size of the data.
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