Media coverage is both a reflection and an influencer of issues that are deemed important to the general public in a given context. Therefore, the level of media coverage on certain developments in the field of sustainable development can serve as an indicator of the extent to which the concept is embedded in public awareness and opinion, at that point in time.
This is the fundamental basis for the online tool, which enables users to analyse and track the frequency with which sustainable development, and associated issues and concepts, appear in the print media across the globe.
The online tool provides a user-friendly interface for users to access the results of a continuous and extensive text mining exercise that is being undertaken here at Queen’s University. In summary, a comprehensive search has been undertaken in 115 newspapers covering 41 countries for key words related to sustainable development. The database draws from articles as far back as 1990 to present. In mid-2010, this reflected a search of 69,000,000 articles from 369,000 newspaper issues.
To collect the data, standard text mining tools such as LexisNexis were used to conduct the keyword searches. For the search terms, we compiled clusters of key terms related sustainable development, e.g., sustainability, sustainable development, and business ethics, and searched for these and their translations into eight different languages (i.e., English, French, German, Spanish, Portuguese, Dutch, Danish, and Italian). To prevent double-counting, the data reflects articles rather than words. So if sustainability is mentioned 10 times in one article, that is shown as a single hit; the same would occur if sustainability was only mentioned once in the article.
The search reports obtained from the keyword search were subsequently processed by a text mining routine constructed on the basis of Microsoft Excel. This text mining routine enabled us to link every article that contained a specific search term with the publication date and publication title.
For a list of the newspapers that have been included in the analysis please click here. For more information on the data mining process please click here.