Cultural motifs (Framing)
Authors: Knorr Charlotte , Pentzold Christian 
Published: June 2024

This variable describes the cultural pattern of a text/article. The concept of “cultural motifs” refers to phenomena which are culturally embedded and which support interpretations that are normally associated with “culture”. Cultural motifs are the core of a statement in the text.
Entry connected to
framing devices
causal attributions
Field of Application/Theoretical Foundation
As the core of a frame package, cultural motifs are seen as the anchor of a “frame” (Entman, 1993) and not as a frame itself. A cultural motif can be understood as “the implicit cultural phenomenon that defines the package as a whole, for instance, a value or an archetype” (Van Gorp, 2010, p. 97-98). Cultural motifs are often accompanied by the problem definition and/or a moral evaluation. But, in contrast to a problem definition, a causal attribution and/or a moral evaluation in a journalistic or a user statement, cultural motifs are rarely found in concrete words in the text. Cultural motifs serve as a sort of pivot, around which all framing and reasoning devices “revolve”. The concept can be used to identify the cultural assumptions around which a journalistic text, its problems and responsibilities, are built.
References/Combination with other methods of data collection
Cultural motifs are often used as a variable to identify frames and their structure. As they require an understanding and knowledge of the topics of the texts that are to be analyzed manually, no automated measurement procedures have yet been developed.
Example studies: Pentzold & Knorr (2024); Pentzold & Fischer (2017); Van Gorp & Vercruysse (2012)
Information on Van Gorp & Vercruysse, 2012
Authors: Baldwin Van Gorp and Tom Vercruysse
Research questions: What are the dominant frames used to represent dementia and what alternative frames could be proffered?
Object of analysis: An inductive frame analysis to examine the various ways in which the media define dementia both in news aggregates and in audio-visual material from the internet. The aim is to find indications of how and what conceptions people gain of dementia through news, audiovisual material, novels, and public health brochures. Hereby, the analysis followed an initial three-step coding procedure: First, the authors conducted the material inductively by coding key terms, with regular feedback moments to discuss potential divergences. This first phase ended when no new frames were detected, followed by an axial coding procedure of the whole material during phase two. Here, every new passage from the material had to be connected to at least one frame package so to verify the pre-defined frames from phase one. Third and lastly, frame packages were created by linking both reasoning devices and framing devices with a cultural theme.
Time frame of analysis and analyzed media type: The sample consisted of a representative selection of Belgian newspaper coverage from March 1, 2008 to July 1, 2010. In addition, books about dementia (n=20) were examined together with (audio-)visual material (n=14) based on the search results for “dementia” on www.imdb.com and www.youtube.com. Finally, public health brochures of dementia were part of the sample (n=15).
Information about variable
Variable/name definition: Frames/frame packages that define dementia
Scale: Nominal
Level of analysis: In the beginning by paragraph level, then the whole text as the frames began to emerge more clearly.
Sample operationalization: A frame / frame package consists of seven elements. These are the following: (1) cultural theme; (2) definition of the problem; (3) cause (why is it a problem?); (4) consequences; (5) moral values involved; (6) possible solutions/actions; (7) metaphors, choice of vocabulary.
Values: The qualitative analysis resulted in a total of twelve frame packages (six frames and six counter-frames). Each consists of a central cultural theme, a definition of dementia, the causes and possible consequences, the moral evaluation and possible future scenarios of dementia. (1A. Dualism of body and mind vs. 1B. Unity of body and mind; 2; The invader; 3. The strange travelling companion; 4A. Faith in science vs. 4B. Natural ageing; 5. The fear of death and degeneration; 6. Carpe diem; 7A. Reversed roles vs. 7B. Each in turn; 8A. No quid pro quo vs. 8B. The Good Mother)
Reliability: First, both authors coded independently of each other and met to discuss differences. This resulted in tentative frames which were used for further qualitative research of the material. Then, the frames found were discussed with experts (in a workshop setting).
Codebook: Description of the sample (newspapers and audiovisual material) can be found at the end of the article (appendix of Van Gorp & Vercruysse, 2012).
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 newspapers and magazines from three countries: South Africa, Germany, and the United States. No visual material was collected or examined. In total, material from 26 newspapers and magazines was analyzed. The time frame ranged from 2011 to 2020 (N=1,456). Articles had to contain the keywords “big data” or “dataf*” (e.g., datafication, datafied) in the headline, sub-headline and/or first paragraph (sampling criteria).
To analyze the frames manually, it was assumed that frames are organized according to three levels analysable in a press text. First, the reasoning devices, followed by – secondly – the framing devices (references, argumentation patterns, idioms, metaphors, topoi) and – thirdly – the cultural motifs. Coming from a socio-constructionist approach, a cultural motif is the anchor of an idea expressed in a text (Van Gorp, 2010, p. 7). It is connected to a social problem. To understand this connection, the problem definition, causal attribution, treatment recommendation, and moral evaluation associated with the coded cultural motif were analyzed (cf., Van Gorp, 2010, p. 91-92; Entman, 1991, p. 52). These four elements are the reasoning devices of a frame. They are accompanied by the so-called framing devices which are stylistic devices, catchphrases, metaphors, and references. To that end, for the manual frame analysis on Big Data in the press aggregates, we developed codes for framing devices (1), reasoning devices (2), and cultural motifs (3). All three elements form part of a frame package (Van Gorp, 2007, 2010).
To build the frame packages, we followed procedures of both block modeling and cluster analysis. First, a block modeling was conducted – as introduced by White for structural analyses (White et al., 1976) – to prepare the data set for the cluster analysis. Then, the coded cultural motifs, the reasoning devices, and the framing devices that correlated strongly in the data set (a total of 9 variables and 34 codes) were chosen. With that, a hierarchical cluster analysis (Ward method) was conducted (Matthes & Kohring, 2008, p. 268). Binary variables were calculated for each of the codes of the nine variables.
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: Cultural Motif
Scale: Nominal
Level of analysis: Whereas the formal categories in the manual content analysis were coded at the level of a single news item, the individual frame elements were coded at the level of propositional units. A propositional unit (= analysis unit) can be connected to several codes that are assigned to either a framing device, a reasoning device or a cultural motif. Not all but some frame elements had to be present in the news item, and at least one reasoning device. Furthermore, at least one reasoning device should be tied to a framing device and/or cultural motif to prove that the propositional unit contains semantic relationships and not just elements of “raw text” (van Atteveldt, 2008, p. 5).
Operationalization: Cultural motifs are the cultural core of a social idea framed in a text. In the project we assume the following six core cultural motifs. These cultural motifs were developed as part of a critical discourse analysis of 17 bestsellers on the subject of Big Data/datafication (published between 2013 and 2017, Pentzold & Knorr, 2023). Big data is needed for/becomes/will be… [cultural motif 1-6] (multiple motifs can be coded per article; but only one per propositional unit).
Values: see Table 1.
Reliability: α = .810 [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].
Table 1
Values used for the variable cultural motif linked to Big Data as a cultural phenomenon (Pentzold & Knorr, 2024).

Code

Cultural motif

Description

1

innovations for societal progress and/or personal advancement

key to a narrative of an efficient and strong society (rapid technological developments/ innovations for, e.g., politics, journalism, economy. There is an underlying assumption of progress due to technological innovations, for instance in the field of education, health, but also mental health.

2

a shift in surveying and datafying society

refers to the revolutionary character of Big Data. Big Data is associated with a historical turning point, notions of revolution and change. A new society is to be built and maintained with the help of Big Data. People shall be divided into groups or patterns with the help of artificial intelligence and automation. Data stands for facts and replaces gut feeling.

3

preventing wrongs

negotiation processes on how Big Data can be used to prevent crimes and wars, and to predict risks. The deployment of technologies justifies police operations and changes political communication (potentially with references to Data Justice).

4

(discrete) surveillance

counter-theme to the cultural motif “preventing wrongs”, this motif is subject to negotiation processes to what extent data are used and may/should be used for surveillance. For instance, Data are needed for and, moreover, justified by political, military, and corporate/economic oversight and intelligence. It is not just about justifying mass surveillance, but also about addressing its legitimacy on a fundamental level because forms of mass surveillance may threaten democracy.

5

profits and prediction

economic dimension of Big Data. The value of the data is to be exploited and sold. Not just data but metadata of the users are retailed. “Clever software” affords identifying and mobilizing potential voters and enables target group-specific addressing and voter predictions, for example in election campaigns (behavioural microtargeting).

6

civic agency and empowerment

focus on social principles in dealing with data and the preservation of privacy, and how it can be guided by a transparent data policy. Key values are privacy and the protection of private data plus people´s own initiative and empowerment to act together as publics (social data, human judgement).

7

Negative consequences of Big Data and their critics

-98/-99

Something else /nothing detected

(e.g., artificial intelligence/AI; globalization, robots, digitalization, digitization, cyberwar, technologies)

Note: Multiple motifs can be coded per article; but only one per propositional unit.
References
Entman, R. M. (1991). Framing U.S. Coverage of International News: Contrasts in Narratives of the KAL and Iran Air Incidents: Symposium. Journal of Communication, 41(4), 6–27.
Gamson, W. A., & Modigliani, A. (1989). Media Discourse and Public Opinion on Nuclear Power: A Constructionist Approach. American Journal of Sociology, 95(1), 1–37. https://www.jstor.org/stable/2780405
Jasanoff, S. (2015). Future Imperfect. In S. Jasanoff & S. Kim (Eds.), Dreamscapes of Modernity (pp. 1–33). Chicago: University of Chicago Press.
Matthes, J., & Kohring, M. (2008). The Content Analysis of Media Frames: Toward Improving Reliability and Validity. Journal of Communication, 58(2), 258–279. https://doi.org/10.1111/j.1460-2466.2008.00384.x
Pentzold, C., & Fischer, C. (2017). Framing Big Data: The discursive construction of a radio cell query in Germany. Big Data & Society, July-December, 1–11. https://doi.org/10.1177/2053951717745897
Pentzold, C., & Knorr, C. (2023). When data became big: revisiting the rise of an obsolete keyword. Information, Communication & Society, 27(3), 600–617. https://doi.org/10.1080/1369118X.2023.2227673
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. https://www.sozphil.uni-leipzig.de/en/institut-fuer-kommunikations-und-medienwissenschaft/professuren/chair-of-media-and-communication/forschungs-und-praxisprojekte/framing-big-data
van Atteveldt, W. (2008). Semantic network analysis: Techniques for extracting, representing and querying media content. SIKS dissertation series: no. 2008-30. BookSurge.
Van Gorp, B. (2007). The Constructionist Approach to Framing: Bringing Culture Back In. Communication Research, 57, 60–78.
Van Gorp, B. (2010). Strategies to Take Subjectivity Out of Framing Analysis. In P. D´Angelo & J. A. Kuypers (Eds.), Communication Series. Doing News Framing Analysis: Empirical and Theoretical Perspectives (pp. 84–109). New York: Routledge.
Van Gorp, B., & Vercruysse, T. (2012). Frames and counter-frames giving meaning to dementia: A framing analysis of media content. Social Science & Medicine (1982), 74(8), 1274–1281. https://doi.org/10.1016/j.socscimed.2011.12.045
White, H. C., Boorman, S. A., & Breiger, R. L. (1976). Social Structure from Multiple Networks. I. Blockmodels of Roles and Positions. American Journal of Sociology, 81(4), 730–780. http://www.jstor.org/stable/2777596