Paper year
2025
Paper dossier
Unheard melodies and emotional peaks in <i>Let It Go</i> and <i>Show Yourself</i>: a multimodal sentiment analysis
Detail viewSimilarity handoff
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Citations
1
Authors
0
Topic labels
0
Source readout
Source and corpus status
Venue
Unknown venue
Source slug
unknown
Corpus placement
Controlled edge slice
Similarity rows
Not available yet
Ranking readout
Where this paper lands in the current run
Run shadow-generalization-product-candidate-ranking-v1Top 50 surfaced
This block uses the same resolved ranking run as Recommended. Ranks here are materialized paper_scores ranks; live Emerging may be reordered by the bounded ML scorer. Family rank is global within each family, but rank is only shown when this paper lands inside the surfaced top 50.
Families present
2
Top 50
0
Run label
shadow-generalization-product-candidate-ranking-v1
Snapshot
source-snapshot-shadow-generalization-v1-20260521
Scope: family global | run rank-83787b91ef
Emerging
Present in run, outside top 50
Emerging: embedding slice fit vs included-corpus centroid (title+abstract), plus citation velocity and topic growth; not universal relevance. Bridge signal not used here.
Signals: semantic=0.8412, citation_velocity=0.0600, topic_growth=0.0000, diversity_penalty=0.0000
Why this surfaced | 3 used | 1 penalty | 1 not computed
Embedding slice fit (corpus centroid)used
Embedding slice fit (corpus centroid): high; used in final ranking (contribution to score: 0.1682)
Recent attentionused
Recent attention: low; used in final ranking (contribution to score: 0.0300)
Topic momentumused
Topic momentum: low; used in final ranking (contribution to score: 0.0000)
Cross-cluster signalnot computed
Cross-cluster signal: not computed for this run
Similarity penaltypenalty
Similarity penalty: reduces score when non-zero (contribution to score: 0.0000)
Bridge
Present in run, outside top 50
Multi-topic paper in active topics; no cluster_version on this run so bridge_score was not computed.
Signals: citation_velocity=0.0600, topic_growth=0.0000, diversity_penalty=1.0000
Why this surfaced | 2 used | 1 penalty | 2 not computed
Semantic matchnot computed
Semantic match: not computed for this run
Recent attentionused
Recent attention: low; used in final ranking (contribution to score: 0.0210)
Topic momentumused
Topic momentum: low; used in final ranking (contribution to score: 0.0000)
Cross-cluster signalnot computed
Cross-cluster signal: not computed for this run
Topic breadth penaltypenalty
Topic breadth penalty: reduces score when non-zero (contribution to score: -0.2000)
Under-cited
No materialized row for this family in the resolved run
This paper did not surface into the current materialized family row set.
Abstract
Abstract This research endeavor presents a rigorous interdisciplinary investigation into the emotional and narrative functions of " Let It Go " ( Frozen ) and " Show Yourself " ( Frozen II ), addressing a gap in scholarship that primarily relies on qualitative interpretations. Employing a novel multimodal approach, the study integrates tools from Natural Language Processing (NLP) and Computer Vision to analyze the complex interplay of lyrical, musical, and visual elements. Recognizing the inherently multimodal nature of film and music, it moves beyond traditional unimodal sentiment analysis, which often simplifies emotional complexity. More specifically, it introduces a novel multimodal framework for music sentiment analysis, integrating textual analysis (using BERT and VADER), visual analysis (using Facial Emotion Recognition), and auditory analysis (using Music Information Retrieval techniques). This synergetic approach affords a more holistic understanding of emotional expression than unimodal methods, addressing limitations of existing categorical and dimensional sentiment analysis approaches. Further, it provides a quantitative analysis of emotional trajectories within the selected Frozen songs, complementing existing qualitative interpretations focused on themes of gender, empowerment, and self-discovery.
Authors
No authors available.
Neighborhood labels
Topics
0 labels
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Neighbor surface
Similar papers
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Next handoff
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01
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02
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03
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