Department of Political Science, University of Gothenburg and Gavagai, Stockholm
Issue framing has become one of the most important means of elite influence on public opinion. In this paper, we introduce a method for investigating issue framing based on statistic analysis of large samples of language use. Our method uses a technique called Random Indexing (RI), which enables us to extract semantic and associative relations to any target concept of interest, based on co-occurrence statistics collected from large samples of relevant language use. As a first test and evaluation of our proposed method, we apply RI to a large collection of Swedish blog data and extract semantic relations relating to our target concept “outsiders”. This concept is widely used in the public debate both in relation to labour market issues and socially related issues.
In: Bertie Kaal, Isa Maks and Annemarie van Elfrinkhof (eds.) From Text to Political Positions: Text analysis across disciplines, John Benjamins Publishing Company, 2014, pp. 71–92.