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Climate change discourse in mass media: application of computer-assisted content analysis

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Abstract

Content analysis of mass media publications has become a major scientific method used to analyze public discourse on climate change. We propose a computer-assisted content analysis method to extract prevalent themes and analyze discourse changes over an extended period in an objective and quantifiable manner. The method includes the following: (1) sample selection; (2) preparation of the text segments for computer processing; (3) identifying themes in the texts using exploratory factor analysis; (4) combining identified themes into higher order themes using confirmatory factor analysis; (5) using factor scores to interpret themes obtained from public discourse; and (6) tracking the main themes of public discourse through time. We apply the proposed methodology to the analysis of the articles published in the New York Times on climate change during the period from 1995 to 2010. We found a gradual decline in the volume of material within the “Science” topic and an expansion of themes classified under the “Politics” topic.

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Notes

  1. Compare the wording “The balance of evidence suggests that there is a discernible human influence on the global climate” in SAR with “Thus the observed [temperature] increase could be largely due to this natural [climate] variability; alternatively this variability and other human factors could have offset a still larger human-induced greenhouse warming” in the 1990 IPCC First Assessment Report (FAR).

  2. LexisNexis is the most frequently used database in the social sciences (Deacon 2007). However, it does not contain all items that appeared in the “physical” version of some of the newspapers (Deacon 2007), and some of the entries were duplicates.

  3. E.g., an article on non-for-profit organizations was selected based on a sentence: “Starting with core campaigns in the 1970s to make the air and water cleaner and protect natural resources, those groups in the 1980s established large and elaborate programs to address a wide array of more scientifically complex and politically difficult issues like global warming and saving obscure animals.” (Schneider, K., Big Environment Hits a Recession. NYT, 1.1.1995)

  4. An example of a full factor would be the Kyoto Protocol (Cronbachs’ α = .74), which combines the following variables: Kyoto, protocol, treaty, ratification, ratify, reject, Russia. For clarity, we provide words from here on, but in reality the variables contained word stems only.

  5. Examples of stable word combinations would be NAVI and ship or Gulf and coast. Though closely associated, these words did not define a topic and could not be meaningfully interpreted.

  6. Some of the factors identified by a single variable were lacking other variables that were too infrequent in the original texts. The words that might otherwise “fill in” were not included in the variable list due to an arbitrary level of word frequency cutoff.

  7. Some variables (e.g., environment) were too general to associate with any particular factor alone.

  8. As measured by WFI (discussed in “Dynamics of climate change discourse”).

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Authors and Affiliations

  1. Department of Earth Systems Science and Policy, University of North Dakota, Stop 9011, Grand Forks, ND, 58202-9011, USA

    Andrei P. Kirilenko

  2. The Department of Tourism, Recreation and Sport Management, University of Florida, P.O. Box 118208, Gainesville, FL, 32611-8208, USA

    Svetlana O. Stepchenkova

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  1. Andrei P. Kirilenko
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  2. Svetlana O. Stepchenkova
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Correspondence to Andrei P. Kirilenko.

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Kirilenko, A.P., Stepchenkova, S.O. Climate change discourse in mass media: application of computer-assisted content analysis. J Environ Stud Sci 2, 178–191 (2012). https://doi.org/10.1007/s13412-012-0074-z

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