Press Sections in Online Newspapers (Formats and Genre)
Authors: Knorr Charlotte , Pentzold Christian , Hallmann Tabea 
Published: June 2024

The following press sections are a collection that emerged from an inductive-deductive analysis of 26 periodicals from Germany, South Africa and the US. Overlaps on big topics were found and sub-topics assigned accordingly (Pentzold & Knorr, 2024).
Field of Application/Theoretical Foundation
Journalists usually publish their articles in topic-specific sections. The decision on the section, i.e., the journalistic placement within a thematic context, can already be seen as part of framing (preframing) on the part of the publishers, journalists and the recipients (Scheufele, 2004).
Example studies: Pentzold & Knorr (2024) & Wessler et al. (2016)
Information on Wesser et al., 2016
Authors: Hartmut Wessler, Antal Wozniak, Lutz Hofer, and Julia Lück
Research questions: Which topics and frames as well as which visual elements such as photos, diagrams and graphics are present in the press reporting on climate change in the context of four UN climate conferences (2010-2013), in different countries and coming from different journalists?
Object of analysis: A comparative issue-specific multimodal news frame analysis of climate change coverage around the UN Climate Change Conferences in Cancún, Mexico (COP 16, 2010), Durban, South Africa (COP 17, 2011), Doha, Qatar (COP 18, 2012), and Warsaw, Poland (COP 19, 2013). Both textual and visual content elements were analyzed and then incorporated into a joint cluster analysis.
Time frame of analysis: Event-based sampling around the UN Climate Change Conferences in Cancún, Mexico (COP 16, 2010); Durban, South Africa (COP 17, 2011); Doha, Qatar (COP 18, 2012); and Warsaw, Poland (COP 19, 2013).
Analyzed media type: Newspapers from five countries: Brazil (Folha de Sao Paolo, O Globo), Germany (Süddeutsche Zeitung, Frankfurter Allgemeine Zeitung), India (Times of India, The Hindu), South Africa (Daily Sun, The Star), the United States (New York Times, Washington Post)
Information about variable:
Variable/name definition: Section of newspaper / magazine / news website [Section]
Scale: Nominal
Level of analysis: News article
Sample operationalization: The position of the press article was coded, referring to its placement in the overall press outlet (front page, inside the newspaper, commentaries etc. distinguishable by distinct layout features such as a different font for headlines and the naming of authors).
Values: 1 Politics; 2 Economy / Business; 3 Opinion / Letters to the editor; 4 Culture & Arts / Feuilleton / Media; 5 Local news; 6 Science/Technology; 7 Environment; 8 Miscellaneous /Human interest; 9 Supplement with editorial responsibility of media outlet; 997 Other; 998 Unclear; 999 Not applicable
Reliability: In sum, intercoder reliability achieved at least a .70 level (six coders).
Codebook: Wessler et al. (2016)
Information on Pentzold & Knorr, 2024
Authors: Christian Pentzold and Charlotte Knorr
Research questions: With which imaginaries do journalistic reports make sense of Big Data? (RQ1) How do these imaginaries evolve over time? (RQ2) To what extent are the imaginaries similar or different across countries? (RQ3)
Object of analysis [and analyzed media type]: The project Framing Big Data (DFG 2021-2024) analyzed the media-communicatively articulated frames on “Big Data” in online press aggregates of newspapers and magazines in three countries: South Africa, Germany and the United States. No visual material was collected or examined. In total, the coded press aggregates of 26 newspapers and magazines were analyzed. The period of collected press articles was from 2011 to 2020 (N=1,456 press articles). Hereby, the online press articles had to contain the keywords “big data” or “dataf*” (e.g., datafication, datafied) in the headline, sub-headline and/or first paragraph (inclusion criteria).
Time frame of analysis: 2011, Jan 1 – 2020, Dec 31
Analyzed media type: Online press aggregates from newspapers and magazines in three countries: South Africa, Germany, and the United States. In sum, the coded press aggregates were sampled from 26 periodicals.
Codebook: Public_Codebook_FBD_fin.pdf
Information about the variable
Variable name/definition: Press sections in online newspapers. This variable was created from a compilation of sections found in most newspapers, supplemented by newspaper-specific subsections. It is a comprehensive collection of all sections present in newspapers from three countries (Germany: Frankfurter Allgemeine Zeitung, Süddeutsche Zeitung, ZEIT online, WirtschaftsWoche, Handelsblatt, taz, Welt online, Spiegel online, wired, c’t; South Africa: NAG, The Star, Financial Mail, Business Day, Sunday Times, Brainstorm Magazine, Tech Central, Mail & Guardian, Stuff Magazine; USA: New York Times, Washington Post, Financial Times, Wall Street Journal, Forbes, Newsweek, Brainstorm). Since some newspapers – such as Süddeutsche Zeitung or The Star – have detailed sections for specific regions and others like Forbes, Stuff Magazine and Handelsblatt feature sections on specific technical/economic topics, all editorial sections were recorded by hand and manually bundled according to superordinate categories (e.g., Economics, Science, Success, Society) and subcategories to be able to map the characteristic sections across newspapers. The aim was to be able to also code sections that are specific to one magazine while assuring combability with the structure of other outlets.
Scale: Nominal
Level of analysis: Formal level (press article), coded as press product and as part of the discourse (formal variables, content variables; article unit)
Sample operationalization: Code the press section that is depicted on the top of the article. Not every journal clearly depicts the section their articles are published in (especially online). Do not confuse key words with sections.
Values: 1. Politics (domestic and foreign affairs, network policies, courts and law, fact checks); 2. Economics (Banks, Energy, Industry, Stocks, Taxes, Real Estate, Cars); 3. Technology/Science (Knowledge, Research, IT, Digital, Traffic and Mobility, Work, Ecology); 4. Business (Finances, Companies, Investments); 5. Culture (Media, Books, Movies, Art, Travel, Fashion, Food, Regional); 6. Society (Style, Discover, Research, Reports, Ideas, ZEITmagazin, ze.tt, Z2X, Podcasts, Feuilleton); 7. Opinion (Columns, Comments, Guest Articles, Debate) ; 8. Global Crisis (Ukraine, Covid-19, Climate change); 9. Success (Management, Coaching, Trends, Career, Job, Universities); 10. Health/Medicine; 11. Regional; 12. Headlines; 13. Sports; -97 not visible; -98 unclear; -99 not applicable (one code per news article)
Reliability: α = 1.00 [Krippendorff’s alpha, intercoder reliability. A total of seven reliability tests were conducted, five of them during the coding phase and two as part of two pretests. Five coders were involved in four tests, four coders were involved in three tests. All tests were conducted in the period July 2022 to December 2022].
References
Jasanoff, S. (2015). Future Imperfect. In S. Jasanoff & S. Kim (Eds.), Dreamscapes of Modernity (pp. 1–33). Chicago: University of Chicago Press.
Pentzold, C. & Knorr, C. (2024). Making Sense of “Big Data”: Ten Years of Discourse Around Datafication (ICA 2024, 74th Conference, Gold Coast, Australia).
Pentzold, C., & Knorr, C. (2021-2024). Framing Big Data (DFG). Leipzig University.
Scheufele, B. (2004). Framing-effects approach: A theoretical and methodological critique. Communications, 29(4), 401–428.
Wessler, H., Wozniak, A., Hofer, L., & Lück, J. (2016). Global Multimodal News Frames on Climate Change: A Comparison of Five Democracies around the World. The International Journal of Press/Politics, 21(4), 423–445. doi: 10.1177/1940161216661848