VLRC Project

Visual Language Research Corpus

How do the drawing systems and sequential images of cultures around the world differ? Is there systematicity underlying the diversity of structures in these different visual languages? To answer these questions we have been analyzing comics from around the world. 

The Visual Language Research Corpus (VLRC) is a corpus of annotated comics analyzing the structures in visual languages of the world. The VLRC is made up of ~36,000 coded panels from 350+ comics from Europe, Asia, and the United States, across time periods (1940-present), and various genres. It also includes annotation of the entire run of the Calvin & Hobbes comic strip.

The content of annotations includes coding of panel framing, semantic relations between panels, external compositional structure (page layout), multimodality, and a variety of other structures of visual languages

We are continuing corpus research with the TINTIN Project funded by a European Research Council Starting Grant.

VLRC Framing Data

Want to read more about the VLRC Project? Check out our VLRC related blog posts with periodic updates and insights.

Repository for VLRC Data: DataverseNL

Publications using the VLRC

An extensive analysis of the VLRC is made in Neil Cohn’ book, The Patterns of Comics, out in Fall 2023. These publications also report patterns found in the VLRC:

  • Cohn, Neil, Bruno Cardoso, Bien Klomberg, and Irmak Hacımusaoğlu. 2023. The Visual Language Research Corpus (VLRC): An annotated corpus of comics from Asia, Europe, and the United States. Language Resources and Evaluation. (Read online)
  • Hacımusaoğlu, Irmak, Bien Klomberg, and Neil Cohn. 2023. Navigating Meaning in the Spatial Layouts of Comics: A cross-cultural corpus analysis. Visual Cognition. (Read online)
  • Cohn, Neil, Irmak Hacımusaoğlu, and Bien Klomberg. 2023. The framing of subjectivity: Point-of-view in a cross-cultural analysis of comics. Journal of Graphic Novels and Comics. 14 (3):336-350 (Read online)
  • Hacımusaoğlu, Irmak and Neil Cohn. 2022. Linguistic Typology of Motion Events in Visual Narratives. Cognitive Semiotics. 1-26. (Read online)
  • Klomberg, Bien, Irmak Hacımusaoğlu, and Neil Cohn. 2022. Running through the Who, Where, and When: A cross-cultural analysis of situational changes in comics. Discourse Processes. (Read online)
  • Cohn, Neil. 2020. Who Understands Comics?: Questioning the Universality of Visual Language Comprehension. London: Bloomsbury.
  • Cohn, Neil. 2019. Structural complexity in visual narratives: Theory, brains, and cross-cultural diversity. In Grishakova, Marina and Maria Poulaki (Ed.). Narrative Complexity and Media: Experiential and Cognitive Interfaces. (pp. 174-199). Lincoln: University of Nebraska Press. (PDF)
  • Cohn, Neil, Jessika Axnér, Michaela Diercks, Rebecca Yeh, and Kaitlin Pederson. 2019. The cultural pages of comics: Cross-cultural variation in page layouts.  Journal of Graphic Novels and Comics. 10(1): 67-86 (PDF)
  • Cohn, Neil, Ryan Taylor, and Kaitlin Pederson. 2017. A picture is worth more words over time: Multimodality and narrative structure across eight decades of American superhero comics. Multimodal Communication. 6(1): 19-37. (PDFVideo Presentation)
  • Cohn, Neil, Vivian Wong, Kaitlin Pederson & Ryan Taylor. 2017. Path salience in motion events from verbal and visual languages. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (pp. 1794-1799). Austin, TX: Cognitive Science Society. (PDFPoster PDF)
  • Pederson, Kaitlin and Neil Cohn. 2016. The changing pages of comics: Page layouts across eight decades of American superhero comics. Studies in Comics. 7(1): 7-28. (PDFVideo Presentation)

Contributors

Several publishers have contributed to this research by generously donating comics to our corpus of research materials. They include:

Their support is greatly appreciated! If you or your company would like to donate materials to our current research, please contact me.

Contributors

The VLRC was coded by several student researchers at UC San Diego and Tilburg University. They include:

Jessika Axnér, Justin Brookshier, Michaela Diercks, Mark Dierick, Sean Ehly, Ryan Huffman, Kaitlin Pederson, Ryan Taylor, Lincy van Middelaar, Vivian Wong, Rebecca Yeh