Innovation
Methods, ideas, or system contributions that make the work stand out.
multi-modal analysis
brain rot memes
cross-linguistic comparison
CRIB dataset
video-level dynamics
Dissonant ballerinas and crafty carrots: a comparative multi-modal analysis of Italian brain rot
🤖 AI Summary
This study investigates cross-cultural differences in the appeal of “brain rot” memes between Italy and Romania. Methodologically, it introduces CRIB, a novel Italian–Romanian bilingual multimodal dataset, integrating NLP-based sentiment and absurdity detection, acoustic feature extraction, and visual dynamics assessment to systematically analyze how textual, acoustic, and visual features influence video popularity. The findings reveal that editing rhythm, rather than semantic content, drives virality: fast-paced editing significantly predicts the success of Romanian-language videos, whereas Italian counterparts exhibit stronger negative sentiment, greater rhyming tendencies, and distinct spectrogram characteristics.
📝 Abstract
This paper presents a comparative multi-modal analysis of Italian and Romanian brain rot memes, investigating the factors that contribute to its appeal and the linguistic and cultural distinctions between the two versions. To conduct this analysis, we introduce a multi-modal brain rot dataset named CRIB (Collection of Romanian and Italian Brain rot), a manually curated collection of 240 TikTok videos stratified by language (Italian, Romanian) and popularity, on which we examine textual, acoustic, and visual features. Our findings indicate that popularity is not significantly correlated with textual elements like sentiment, absurdity, or rhyme, or acoustic elements such as vocal features or sentiment of the sound. Instead, in Romanian language, video-level dynamics, specifically faster cutting speeds and a more rapid overall pace, are strong predictors of a video's success. The cross-linguistic analysis reveals significant differences. Italian brain rot is textually more negative, exhibits higher perplexity, and uses more rhyme, while its sound is characterized by higher melodic range and loudness. Romanian audio is spectrally brighter with more erratic pitch variations.
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