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[Commlist] CfP “Images, clusters and types – Making sense of image corpora and dispersed visual practices in and with digital media”

Mon Jun 13 14:54:55 GMT 2022




Reminder
CfP “Images, clusters and types – Making sense of image corpora and dispersed visual practices in and with digital media”: 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. SComS is a peer-reviewed journal of communication and media research with platinum open-access (no article processing charges). *Abstract submission is open until JUNE 15.* 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 /at/ fu-berlin.de).

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?

Further information: https://www.hope.uzh.ch/scoms/announcement/view/36
About SComS
SComS Studies in Communication Sciences (SComS) is a peer-reviewed, platinum open access journal for communication and media research. It publishes original research from a variety of traditions, disciplines, contexts, and methodologies, thereby addressing and illuminating communication in its various facets. Neither authors nor readers are required to pay any fee. SComS is jointly edited by the Swiss Association of Communication and Media Research (SACM) and the Faculty of Communication, Culture and Society of the Università della Svizzera Italiana (USI Lugano). SComS is published by Seismo Verlag and HOPE (Hauptbibliothek Open Publishing Environment). For more information, see https://www.hope.uzh.ch/scoms/index


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