Tenth International Conference on Communication & Media Studies

With advancements in media technologies, neural networks and vision-language models (VLMs) present possibilities for art historians, particularly in automating style prediction and historical classification. This paper synthesizes findings from two studies we conducted to critically assess whether these models can meaningfully interpret stylistic transitions in art history. In our first study, we implemented a neural network trained on the WikiArt dataset to evaluate its capacity to capture temporal continuity and stylistic coherence across different art periods. This analysis probes whether such computational representations could assist art historians in mapping stylistic evolution, while acknowledging significant challenges in interpretability and historical nuance. Our second study examines VLMs on zero-shot classification tasks, including art style, artist attribution, and period dating. Using two public benchmarks and a curated test set, which includes pivotal artworks frequently studied by art historians, we evaluated these models' ability to handle the complexities of artistic composition and stylistic diversity. While promising, VLMs reveal limitations in grasping the subtleties that define art, raising concerns about oversimplification and misinterpretation. Our findings elucidate the potential and constraints of AI in art historical research. By integrating neural networks and VLMs as supplementary instruments rather than substitutes, we address the complexities associated with the deployment of media technologies in a field characterized by interpretive richness. The objective of this paper is to prompt reflection on the potential of AI to advance art historical practice, while also cautioning against an undue reliance on these emerging technologies.

Digital Culture's Impact on Brand Communication

Jūlija Surikova
Paper Presentation in a Themed Session

This research explores how digital culture influences brand communication on social media, specifically focusing on placemaking efforts within Facebook. The author of the research employed a mixed-methods approach, combining content analysis of Facebook page publications of a placemaking project in Tallinn with in-depth interviews with brand managers and communication strategists on their views on how brand voice has been affected by becoming primarily digital. The content analysis aimed to identify strategies and tactics applied in communication to engage with their audiences in a digital context. Simultaneously, the interviews yielded valuable insights into the strategic decisions underlying these communications and the influence of wider cultural trends in the digital realm. The findings reveal that digital culture significantly impacts how brands craft their voices to foster a sense of place and community online. The study highlights specific tactics that are effective in engaging diverse audiences and underscores the importance of adaptability and cultural sensitivity in online brand communications. This paper contributes to the understanding of digital placemaking and offers practical recommendations for organisations looking to enhance their social media presence in a culturally relevant way.

Participating in the Popular

Marissa Lammon
Paper Presentation in a Themed Session

The examination of media and their audiences has, expectedly, resulted in a diverse body of disciplines, perspectives, paradigms, and research. Although the rapidly changing media landscape has shaped much of media studies, the unique forces of cultural discourse and ideology surrounding specific audiences and specific media platforms presents as a challenge to media researchers. In particular, the discourses surrounding children, animation, and media effects have complicated the understanding of children as media audiences and animation as a pedagogical force. This paper dissects this relationship by integrating cultural analysis into conversations about media and children. It uses systematic review to correlate the classification of animation as a “children’s medium” with the creation and dismissal of adulterated content in animated texts, and places this alongside the ritual behaviors of children concerning media made for them. By exploring how children engage in media rituals, including aspects of character identification, this paper advocates for the conceptualization of popular culture as deeply connected to society in order to properly evaluate the pedagogical nature of media as disseminators of ideology in children’s lives.

A Semiotic Approach to New Forms of Résistance in the AI Era

Gabriel A. Medina-Aguilar
Paper Presentation in a Themed Session

There’s been a debate concerning the epistemological opposition between Semiotics and Semiology. The first one appears to give light to linguistic based problems, while the second one appears to be useful in a wider range of analysis. This work proposes to take both schools of thought in order to find how AI algorithms encounter a semiotic frontier in which profound forms of human communication can resist their exploitation into commercial data. Under a principle called “The Depeche Mode Hypothesis”, this work explains how neuroscience help us to understand the fundamentals of communication and their potential to explore the political dimension of non-linguistic brain activity within new discussions about Digital Cultures.

An Online Ph.D: Huberman Lab and Lex Fridman Podcasts

Sean Mc Cracken, Timothy Kutcher
Poster Session

While obtaining my Ph.D, I have watched and rated all episodes of the Huberman Lab and Lex Fridman Podcasts. The value of these conversations with top scientists and thinkers in the world (and a small number of solo lectures from Huberman) is incredibly immense. These episodes provide listeners confidence, courage, and power to ask questions and obtain significant scientific-based growth. However, due to the large number of podcasts and difficulties finding relevant or interesting episodes, getting started as an outsider and knowing where to go to get the most value--both from an entertainment and learning perspective, is almost impossible. I have complied (albeit somewhat subjective) data as a 'Rating' (1-10, 10 being the 'best podcast ever', 1 being worst--Rating to 1 decimal point) for all podcasts, and a review to justify the rating. I have grouped podcasts based on topic, for example: Neuroscience, Medicine, Biology, Fitness, Nutrition, Physics, Psychology, ect, and collected lists and rankings of relevant podcasts for each category. For someone not familiar with the podcasts, I have determined 'Top 10', and 'Top 50', podcasts as a great place for people to start and not get discouraged by listening to a 'bad' episode. I have also compared my subjective ranking to objective view counts (from youtube) in order to determine 'underrated' (low views, high rating) and 'overrated' (high views, low rating) podcasts. This work will be a significant resource for scientists, especially young persons and those newer to science, to engage with scientific podcasts and leading scientists.

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