Decoding Immersive Cinema
An Integrated Analysis of Narrative Framework and Audience NLP Data in Avatar: Fire and Ash
Bibliographic Data
| ID | 21974492 |
|---|---|
| Authors | Rocío del P Sosa-Fernández (0000-0002-3704-7297, Universidade de Santiago de Compostela, corresponding author), Roi Méndez (0000-0003-2405-6538, Universidade de Santiago de Compostela), Ana Lorena Jiménez-Preciado (0000-0001-9158-0685, Instituto Politécnico Nacional) |
| Year | 2026 |
| Volume | 15 |
| Issue | 5 |
| Pages | 91 |
| Publication date | 2026-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Arts (JOURNAL) |
| Journal identifiers | ISSN: 2076-0752 • E-ISSN: 2076-0752 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/arts15050091 |
| OpenAlex | W7160083742 |
| Language | EN |
| References cited | 19 |
This study examines how immersive narrative resources, whether technological–sensory, narrative–structural, or contextual, are deployed in contemporary blockbuster cinema and to what extent audiences recognize and value them in their evaluations. Using Avatar: Fire and Ash as a case study, the research follows a sequential mixed-methods design. In the first phase, a qualitative film analysis identifies eight types of cognitive immersion, drawing on established theoretical frameworks of narrative immersion. The second phase is quantitative and involves the computational analysis of 1133 valid reviews from Internet Movie Database (IMDb) through Natural Language Processing (NLP) techniques, including n-gram frequency analysis, Latent Dirichlet Allocation (LDA) topic modeling with 3 topics after perplexity minimization, and sentiment polarity analysis. The LDA model reveals three discursive clusters, experiential and emotional, technical and comparative, and critical, with the latter concentrated mostly in low-rated reviews. Text sentiment and numeric ratings show a moderate positive correlation (r = 0.53, p
Convolutional neural network · Discourse analysis · Embodied cognition · Experiential learning · Latent Dirichlet allocation · Narrative · Perplexity · Sentiment analysis · Topic model · Cinema and Media Studies · Media Influence and Health · Narrative Theory and Analysis
| Highly cited | No |
|---|