Studies in Communication Sciences (SComS)

Deadline (Abstracts): June 15, 2022

Edited by Ulla Autenrieth (Fachhochschule Graubünden), Wolfgang Reißmann (FU Berlin), Rebecca Venema (USI Università della Svizzera italiana)

We are seeking contributions for a thematic section of Studies in Communication Sciences (SComS) exploring image corpora and dispersed visual practices in and with digital media.

The search for visual patterns has always been core to the field of visual studies. Already classic scholars like Warburg and Panofsky dedicated much of their work to retrace “pathos formula” (cf. Becker, 2013), or to identify “image types,” defined by Panofsky (1978) as specific forms of representation through which certain actors, actions, events, ideas or themes are visualized. Visual communication researchers have adopted previous works in art history, and have stressed the importance to combine iconographic and iconological expertise with profound knowledge of communication processes and image contexts (Knieper & Müller, 2019).

Research on image types has helped to analyze the highly routinized and conventionalized selection and use of images in news media (Grittmann, 2007, 2019) which iterate topic- or discourse-specific repertoires of images with recurring motifs and representational characteristics with which events, constellations of actors and their (inter)actions are depicted. Here, image types bundle visuals with motifs of similar content or meaning and distinct representational features (Grittmann, 2007; Grittmann & Ammann, 2009, 2011). Importantly, image type analysis has shown a way to link a systematic analysis of quantifiable structures and patterns in data sets with a detailed qualitative analysis and interpretation of representation techniques and compositional features and the manifest and latent meaning of image types (for recent applications, e.g., Brantner, Lobinger, & Stehling, 2020; Pentzold, Brantner, & Fölsche, 2019). Furthermore, key features of corpora based on mass media’s image output were carved out by delineating “generic icons” (Perlmutter, 1998, p. 11), or “key images” and “key image sequences” (e.g., handshakes as gestures to symbolize contracts) (Ludes, 2001). Concurrently, communication research has played out its long-standing expertise in quantitative content analysis, and elaborated new forms of quantitative image (content) analysis (Bell, 2006; Geise & Rössler, 2013; Lobinger, 2012, p. 227–243).

Developments in media environments, media- and image-related practices as well as in methodological tools and procedures call for a re-intensified reflection and work on image types and relational and comparative classification such analyses allow and require. In fact, we have witnessed a major shift in media ecologies as well as in research agendas over the last 10–15 years. Whereas mass media and news media coverage were dominant subjects of inquiry until early 2000s, in recent times more and more research efforts focus on the analysis of the multiple visualities in social media (Hand, 2017; Highfield & Leaver, 2016). Visual communication research contributed with both image analyses of selfies, memes and other visuals (Lobinger & Brantner, 2015), and by increasingly taking image-related practices such as “sharing” into account (Autenrieth, 2014; Gomez-Cruz & Lehmuskallio, 2016; Schreiber, 2017). Studies thus have shed light on how different sorts of visuals are appropriated and used in everyday practices of individuals or in different social entities and have tried to make sense of the constant stream of sorts of images with rather short half-lives which molds our visual media ecologies in times of “networked” and “algorithmic images” (Rubinstein & Sluis, 2008, 2013). When it comes to methods and methodological approaches, computational and digital methods promise to provide new insights and ways of grasping large image corpora and related practices (Niederer & Colombo, 2019). Other contributions explore possibilities to cluster “big image data” corpora (Rogers, 2021) with the help of artificial intelligence, machine learning and diverse sorting tools, supervised and unsupervised strategies (e.g., K-means clustering).

Against this background, the Thematic Section invites to reflect on old and new challenges in analyzing and constructing image types on the level of image contents, and / or in typologizing routinized or conventionalized image-related practices on the level of media and image appropriation and usage.

We welcome both, theoretical reflections on methodology and methods as well as qualitative and quantitative empirical studies or mixed approaches. In particular, the Thematic Section asks:

• How do we build up medium-sized or large corpora of images and practices in digital media environments? How do we develop image types or typologies of image-related practices based on those corpora? Which criteria, elements and relations are essential, which are of secondary relevance – why? What (new) legal and research ethics challenges arise from this? How do we deal with them?

• How do we involve manual and automated forms of coding and analyzing? Which limitations have automated and / or AI-driven forms of image clustering? Are image clusters and image types the same thing, or should we nuance conceptual differences? How are procedures of human and automated coding arranged in appropriate ways, e.g., for mutually correcting the “blind spots” of each other?

• How do we deal with the multitude of actors and contexts involved in producing and sharing images in digital media environments? How do we balance the tension between manifest and latent meanings of image types, and the contextual appropriation of specific representatives in different fields by different actors? How do we bring together people’s everyday practices of using or sorting images, folksonomy or platform-driven classifications, and research-centered, corpus-based results?

Submission guidelines​

SComS welcomes submissions in English, German, French, or Italian. However, English and German are the preferred languages of this Thematic Section. Abstracts should be a maximum of 500 words in length and should explain the main research question(s), scientific literature, methodology, and case studies the authors plan to use. Please submit your abstract via e-mail to wolfgang.reissmann@fuberlin.de.

Manuscripts should be a maximum of 9000 words in length (including the abstract and all references, tables, figures, footnotes, appendices). In addition, authors may submit supplementary material that will be published as an online supplement. Authors are invited to submit original papers that are not under consideration for publication elsewhere.

Articles shall be submitted using the APA reference style, 6th edition. The manuscript itself must be free of any information or references that might reveal the identity of the authors and their institution to allow double-blind peer review. Manuscripts should be submitted via the SComS platform:

https://www.hope.uzh.ch/scoms/about/submissions. We ask authors to carefully prepare submissions according to all rules given in the SComS Submission Guidelines.

Abstract submissions are due June 15 2022. Final acceptance depends on a double-blind peer review process of the manuscripts. The expected publishing date of this thematic section is April / May 2024. However, early submissions that successfully pass the review process will also be immediately published online first.

Contributions that receive positive reviews but are not accepted for the Thematic Section may be considered for publication in a subsequent SComS issue within the General Section

For any further information please contact Wolfgang Reißmann (wolfgang.reissmann@fuberlin.de).

Key dates:

• 15 June 2022:Abstract submission deadline
• 30 June 2022:Decision on acceptance / rejection of abstracts
• 31 October 2022:Full paper submission deadline
• Nov 2022 – Jan 2023:First round of peer review
• 15 March 2023:Resubmission deadline
• March – May 2023:Second round of peer review
• 30 July 2023:Final paper submission
• August 2023:Editorial work / final shape-up

Publication of the Thematic Section is scheduled for April / May 2024

Reference list

Autenrieth, U. (2014). Die Bilderwelten der Social Network Sites. Bildzentrierte Darstellungsstrategien, Freundschaftskommunikation und Handlungsorientierungen von Jugendlichen auf Facebook und Co. Baden-Baden: Nomos.

Becker, C. (2013). Aby Warburg’s Pathosformel as methodological paradigm. Journal of Art Historiography, 9, 1–25. Retrieved from https://doaj.org/article/58b051219d61444cb8171e5ebcc44df4

Bell, P. (2006). Content analysis of visual images. In T. van Leeuwen & C. Jewitt (Eds.), Handbook of visual analysis (pp. 10–34). London, UK: SAGE.

Brantner, C., Lobinger, K., & Stehling, M. (2020). Memes against sexism? A multi-method analysis of the feminist protest hashtag #distractinglysexy and its resonance in the mainstream news media. Convergence: The International Journal of Research into New Media Technologies, 26(3), 674–696. https://doi.org/10.1177/1354856519827804

Geise, S., & Rössler, P. (2013). Standardisierte Bildinhaltsanalyse. In W. Möhring & D. Schlütz (Eds.), Handbuch standardisierte Erhebungsverfahren in der Kommunikationswissenschaft. Wiesbaden: Springer Fachmedien. https://doi.org/10.1007/978-3-531-18776-1_17

Gomez-Cruz, E., & Lehmuskallio, A. (Eds.) (2016). Digital photography and everyday life. empirical studies on material visual practices. Oxford, UK: Routledge.

Grittmann, E. (2007). Das politische Bild. Fotojournalismus und Pressefotografie in Theorie und Empirie. Köln: Herbert von Halem Verlag.

Grittmann, E. (2019). Methoden der Medienbildanalyse in der Visuellen Kommunikationsforschung: Ein Überblick. In K. Lobinger (Ed.), Handbuch Visuelle Kommunikationsforschung (pp. 527–546). Wiesbaden: Springer Fachmedien. https://doi.org/10.1007/978-3-658-06738-0_25-1

Grittmann, E., & Ammann, I. (2009). Die Methode der quantitativen Bildtypenanalyse. Zur Routinisierung der Bildberichterstattung am Beispiel von 9/11 in der journalistischen Erinnerungskultur. In T. Petersen & C. Schwender (Eds.), Visuelle Stereotype (pp. 141–158). Köln: Herbert von Halem Verlag.

Grittmann, E., & Ammann, I. (2011). Quantitative Bildtypenanalyse. In T. Petersen & C. Schwender (Eds.), Die Entschlüsselung der Bilder. Methoden zur Erforschung visueller Kommunikation. Ein Handbuch (pp. 163–177). Köln: Herbert von Halem Verlag.

Hand, M. (2017). Visuality in social media: Researching images, circulations and practices. In L. Sloan & A.

Quan-Haase (Eds.), The SAGE Handbook of Social Media Research Methods (pp. 215–231). London, UK: SAGE. https://dx.doi.org/10.4135/9781473983847

Highfield, T., & Leaver, T. (2016). Instagrammatics and digital methods: Studying visual social media, from selfies and GIFs to memes and emoji. Communication Research and Practice, 2(1), 47–62. https://doi.org/10.1080/22041451.2016.1155332

Knieper T., & Müller, M. G. (2019). Zur Bedeutung von Bildkontexten und Produktionsprozessen für die Analyse visueller Kommunikation. In K. Lobinger (Ed.), Handbuch Visuelle Kommunikationsforschung (pp. 515–526).

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Lobinger, K. (2012). Visuelle Kommunikationsforschung. Medienbilder als Herausforderung für die Kommunikations- und Medienwissenschaft. Wiesbaden: VS.

Lobinger, K., & Brantner, C. (2015). Selfies | In the eye of the beholder: Subjective views on the authenticity of selfies. International Journal of Communication, 9, 1848–1860. Retrieved from https://ijoc.org/index.php/ijoc/article/view/3151

Ludes, P. (2001). Schlüsselbild-Gewohnheiten. Visuelle Habitualisierungen und visuelle Koordinationen. In T. Knieper & M. G. Müller (Eds.), Kommunikation visuell. Das Bild als Forschungsgegenstand – Grundlagen und Perspektiven (pp. 64–78). Köln: Herbert von Halem Verlag.

Niederer, S., & Colombo, G. (2019). Visual methodologies for networked images: Designing visualizations for collaborative research, cross-platform analysis, and public participation. Disena, 14, 40–67. https://doi.org/10.7764/disena.14.40-67

Panofsky, E. (1978/1996). Sinn und Deutung in der bildenden Kunst. Köln: DuMont.

Pentzold, C., Brantner, C., & Fölsche, L. (2019). Imagining big data: Illustrations of “big data” in US news articles, 2010–2016. New Media & Society, 21(1), 139–167. https://doi.org/10.1177/1461444818791326

Perlmutter, D. D. (1998). Photojournalism and foreign policy. Icons of outrage in international crises. Westport, CT: Praeger.

Rogers, R. (2021). Visual media analysis for Instagram and other online platforms. Big Data & Society, 8(1), 1– 23. https://doi.org/10.1177/20539517211022370

Rubinstein D., & Sluis, K. (2013). The digital image in photographic culture: Algorithmic photography and the crisis of representation. In M. Lister (Ed.), The photographic image in digital culture (2nd ed., pp. 22–40), London, UK: Routledge.

Rubinstein, D., & Sluis, K. (2008). A life more photographic: Mapping the networked image. Photographies, 1(1), 9–28.

Schreiber, M. (2017). Audiences, aesthetics and affordances: Analysing practices of visual communication on social media. Digital Culture & Society, 3(2), 143–163. https://doi.org/10.25969/mediarep/13519