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

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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