------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: New Zealand Newspaper Coverage of Climate Change or Global Warming, 2005-2019 - April 2019 2. Authors: Maxwell Boykoff, Meaghan Daly, Lucy McAllister, Marisa McNatt, Ami Nacu-Schmidt, David Oonk, Olivia Pearman 3. Contact Information: Name: Maxwell Boykoff Institution: University of Colorado Boulder Address: Center for Science and Technology Policy Research, 1333 Grandview Avenue, Campus Box 488, Boulder, CO 80309-0488 Email: boykoff@colorado.edu 4. Date of data collection: 2000-2019 -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: This work is licensed under a Creative Commons Attribution 4.0 License. 2. Links to publications that cite or use the data: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/summaries/ 3. Links to other publicly accessible locations of the data: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/form/index.html 4. Recommended citation for the data: Boykoff, M., Daly, M., McAllister, L., McNatt, M., Nacu-Schmidt, A., Oonk, D., and Pearman, O. (2019). New Zealand Newspaper Coverage of Climate Change or Global Warming, 2000-2019 - April 2019. Center for Science and Technology Policy Research, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Web. [Date of access.] https://doi.org/10.25810/JGYV-ZG57.13. --------------------- DATA & FILE OVERVIEW --------------------- 1. File List: A. Filename: MeCCO_new_zealand_dataset_201904.xlsx Short description: Excel version of article counts per source per month for newspaper coverage of climate change or global warming in three Kiwi sources. B. Filename: MeCCO_new_zealand_dataset_201904.csv Short description: CSV version of article counts per source per month for newspaper coverage of climate change or global warming in three Kiwi sources. 2. Relationship between files: Different formats (Excel and CSV) of data with formatting and formulas removed in CSV version. -------------------------- METHODOLOGICAL INFORMATION -------------------------- Updated April 2019 We monitor 89 sources (across newspapers, radio and TV) in 41 countries in seven different regions around the world. We assemble the data by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. These sources are selected through a decision processes involving weighting of three main factors: geographical diversity (favoring a greater geographical range) circulation (favoring higher circulating publications) reliable access to archives over time (favoring those accessible consistently for longer periods of time) Through Lexis Nexis, we search these sources (listed alphabetically): The Age (Australia), The Australian (Australia), Business Day (South Africa), the Courier-Mail (Australia), Daily Mail (Mail on Sunday) (United Kingdom), the Daily Telegraph & Sunday Telegraph (Australia), Dominion Post (New Zealand), the Express and Express on Sunday (United Kingdom), the Ghanaian Chronicle (Ghana), the Globe and Mail (Canada), the Guardian and Observer (United Kingdom), Gulf Daily News (Bahrain), the Herald (Zimbabwe), the Irish Times (Ireland), the Jerusalem Post (Israel), the Korea Times (South Korea), the Los Angeles Times (United States), the Daily Mirror (and Sunday Mirror) (United Kingdom), the Nation (Thailand), National Post (Canada), the New Straits Times (Malaysia), the New York Times (United States), New Zealand Herald (New Zealand), Philippines Daily Inquirer (Republic of the Philippines), the Prague Post (Czech Republic), The Press (New Zealand), The Scotsman (and Scotland on Sunday) (United Kingdom), the South China Morning Post (China), the Straits Times (Singapore), The Sun and The Sun on Sunday (United Kingdom), Sydney Morning Herald (Australia), the Telegraph and Telegraph on Sunday (United Kingdom), the Times and Times on Sunday (United Kingdom), the Toronto Star (Canada), USA Today (United States), the Wall Street Journal (United States), and the Washington Post (United States). We use the Boolean string ‘climate change or global warming’ and the date ranges as well as individual sources selected through the ‘advanced options’ function. For all searches through the Lexis Nexis database, the default option for duplicates was chosen. Through Factiva, we search these sources (listed alphabetically): the Bangkok Post (Thailand), Daily Star (Lebanon), Die Tageszeitung (Germany), El Pais (Spain), El Mercurio (Chile), the Hindu (India), Hindustan Times (India), the Indian Express (India), the Jakarta Post (Indonesia), Japan News (Japan), La Nacion (Argentina), Manila Bulletin (Philippines), the Nation (Pakistan), O Globo (Brazil), The Saigon Times Daily (Vietnam), Süddeutsche Zeitung (Germany), and Times of India (India). We use the Boolean string ‘climate change or global warming’ and the date ranges as well as individual sources selected for all English-languages searches. We conduct individual searches for ‘calentamiento global’ as well as ‘cambio climático’ and then manually search for (and eliminate duplicates. For all English-language searches through the Factiva database, the default option for duplicates was chosen. National-level counts in Japan are undertaken by Midori Aoyagi and Shoko Yamaguchi, from the National Institute for Environmental Sciences (NIES) in Japan. They use the Fujitsu Limited "G-search" database to monitor coverage in Asahi Shimbun, Yomiuri Shimbun and Mainichi Shimbun through the search terms ‘climate change’, ’global warming’, or ‘greenhouse effect, from January 2000 through the present. National-level counts in Spain and Latin America are undertaken by Rogelio Fernández Reyes, member of the research group GREHCCO of the Universidad de Sevilla, and member of the research group MDCS of the Universidad Complutense de Madrid. Rogelio uses My News database (a referent provider of journalistic documentation in Spain) to monitor coverage in El Mundo, La Vanguardia and Expansión through the search terms ‘‘calentamiento global’ or ‘cambio climático’. International and national-level counts in Australia, Canada, India, New Zealand, the United Kingdom and the United States are undertaken by Maxwell Boykoff, Andrew Benham, Meaghan Daly, Rogelio Fernández-Reyes, Lucy McAllister, Marisa McNatt, Ami Nacu-Schmidt, David Oonk, and Olivia Pearman. National-level counts in each of these countries begin in January 2000 with the exception of the following: Dominion Post (July 2002). International counts of the fifty-two noted sources begin in January 2004 with the exception of the following: El Nacional (December 2007); Indian Express (December 2007); The Nation (Pakistan) (June 2004); Gulf Daily News (Bahrain) (May 2008); Philippine Daily Inquirer (September 2004); Ghanaian Chronicle (January 2010); The Herald (Zimbabwe) (January 2010). To arrive at comparable assessments of numbers of articles per month per source, we take the total number of articles each month in each region and divide by the number of sources searched during that month. For the archives that become available after the starting date of January 2004, this denominator changes over time. As some regions contain more sources than others, this 'normalization' process then provides a useful metric for comparisons across regions. These data track newspaper coverage of climate change or global warming in 3 New Zealand newspapers (New Zealand Herald, Dominion Post, and The Press). Updated through April 2019. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: MeCCO_new_zealand_dataset_201904.xslx ----------------------------------------- 1. Number of variables: 232 2. Number of cases/rows: 9 (including header, sums, and citation) Row 1: Header and metadata Row 2-3: Column names (year and month) Rows 4-6: Newspaper data rows Row 7: Normalized sums of region data Row 8: Blank Row 9: Recommended citation 3. Variable List: A. Name: Blank Description: Newspaper titles B-HN. Name: YYYY (Row below includes Month) Description: Article count per month for each newspaper source. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: MeCCO_new_zealand_dataset_201904.csv ----------------------------------------- 1. Number of variables: 233 2. Number of cases/rows: 4 (including header) 3. Encoding: UTF-8 4. Variable List A. Name: Newspaper Description: Title of newspaper source. B. Name: Country Description: Country of newspaper publication. C-HO. Name: YYYY-MM Description: Article count per month (YYYY-MM) for each newspaper source. 5. Missing data codes: blank