Samuli Saarinen1
1 Department of Accounting & Finance, Estonian Business School, Tallinn Harjumaa Estonia
Abstract
This study explores the cultural resonance of Die Hard as a Christmas movie through an innovative data visualization approach. Specifically, it reanimates Hans Gruber’s iconic fall from the Nakatomi Plaza using R and ggplot2, preserving the cinematic moment for future generations and reinforcing its festive reinterpretation. Employing principles of data storytelling and modern animation techniques, the study incorporates visual elements such as holiday lights and thematic titles to enhance the scene’s holiday context. The research examines Die Hard‘s evolving classification as a Christmas movie through cultural and semantic analyses. Content and sentiment analyses of the film, critical reviews, and audience discourse reveal its association with holiday motifs and traditions, highlighting the interplay of setting, themes, and audience reception in defining genre. The animated visualization, assessed through qualitative evaluation and audience testing, demonstrates high fidelity to the original scene, validating the feasibility of creative applications of data visualization tools in popular culture. This interdisciplinary work combines computational modelling, and cultural analysis by illustrating the dynamic nature of genre classification and the power of audience reinterpretation. The study concludes that Die Hard epitomizes a unique festive tradition, offering a compelling case for blending data science with cultural narratives.
Keywords: Christmas, Die Hard, Nuclear Fission, Cat Nip, Modelling and Simulation, Data Visualization
1. Introduction
As it is known modern western style of Christmas has its own traditional characteristics. Some of these characteristics are for example the arrival of a Cosplay actor playing as old man bringing gifts for children, over eating and watching the last minutes of the Die Hard 1, where the main villain Hans Kruger falls from skyscraper on top of old Ford. This event has become the traditional starting point of Christmas. In this paper our aim is to recapture this beautiful moment by using R and ggplot 2 to animate this scene all over again, that it could be saved for the future generations as the VHS tape of the original Die Hard starts to be worn out.
The research question this paper aims to answer could be formalized in a way:” Can the iconic fall of Hans Gruber from Die Hard be effectively visualized and animated using R and ggplot2, and how can such a visualization contribute to the creative application of data visualization tools in popular culture?”
To produce this article, the author has used extensive amount of Red Bull, an LLM and Cat Nip. Which most likely is visible in the structure of the text, but what we could do about it. Maybe call the ghostbusters.
1.1 Background
The debate over topic does Die Hard qualify as a Christmas movie has garnered attention in both popular culture and academic discourse. This literature review examines scholarly perspectives on the film’s classification, focusing on genre theory and cultural analysis.
Scoll (2023) employs Rick Altman’s semantic/syntactic/pragmatic genre framework to analyze Die Hard‘s status. He argues that, despite its initial marketing as a summer action film, the movie has been recontextualized by audiences and media as a Christmas film. This reclassification is attributed to its Christmas Eve setting, thematic elements, and incorporation of holiday motifs, suggesting that genre is fluid and influenced by audience reception.
Wiebe (2024) discusses the cultural significance of Die Hard during the holiday season, noting its emergence as a Christmas tradition for many viewers. He highlights that the film’s association with Christmas is reinforced by its annual broadcast during the holiday season and its integration into festive viewing habits, indicating that cultural practices play a crucial role in genre identification.
Judd (2024) examines the Die Hard debate through the lens of modern genre theory, emphasizing the role of audience interpretation in genre classification. He asserts that while the film was not originally intended as a Christmas movie, its reception and the meanings audiences ascribe to it have transformed its genre status, underscoring the dynamic nature of genre categories.
These analyses collectively demonstrate that Die Hard‘s classification as a Christmas movie is not solely determined by its content or the creators’ intentions but is significantly shaped by audience engagement and cultural context. The film’s setting during a Christmas party, inclusion of holiday music, and themes of family reunion contribute to its festive reinterpretation. This case exemplifies the evolving nature of genre definitions and the impact of societal practices on media categorization.
1.2 Purpose
The purpose of this article is novel. It aims to recapture and preserve the scene from the original Die Hard, with modern motion capture technique, that this moment could be relived again. Also, by using ggplot the animation could be run in multiple types of devices in offline environments, that could widen the scope of possible audience in future to include sewer rats and wombats.
Authors personal motives to produce this paper lies on that author needs to submit one paper on whatever topic to the Cranberry Lemon University. The author also believes that more scientific literature we produce proofing the Die Hard to be Christmas movie, the more the growing body of literature would help and benefit all middle-aged men around the world so that we could more often win the debate whether should we watch Home Alone or Die-Hard trilogy each Christmas Season.
2. Methodology
To conduct our research and answer our research question, the script presented in the appendix was created and it is explained in Methodology section 1. In Section 2 we briefly discuss the content analysis that our modern animation could be compared to the original scene to ensure it’s authenticity. In Methodology 3 section sematic analysis is presented to ensure that our animation would be still considered as Christmas related media.
2.1 Methodology 1
This study employed a computational data visualization approach to create an animated depiction of Hans Gruber’s fall from Die Hard using R and ggplot2. The methodology combines data visualization principles, animation techniques, and cultural analysis to provide a creative representation of a culturally significant cinematic moment. The following steps outline the methodology:
Software and Tools
The animation was created using R, an open-source programming language widely used for statistical computing and data visualization (R Core Team, 2023). The ggplot2 package (Wickham, 2016) served as the foundation for constructing layered visual elements, while the gganimate package (Pedersen & Robinson, 2022) was employed to add animation features.
Conceptual Design
The project was guided by principles of data storytelling (Kosara & Mackinlay, 2013) to ensure that the visualization not only depicted Hans Gruber’s fall but also communicated the cultural significance of Die Hard as a Christmas movie. This includes skyscraper and other extraneous elements, such as festive lights and a thematic title, to emphasize the film’s holiday context.
Data Preparation
Three datasets were created:
Building Data: Coordinates for a polygon representing the Nakatomi Plaza.
Window Data: A grid of rectangles to mimic windows on the skyscraper facade.
Hans Gruber’s Fall Data: A time-series dataset specifying the x and y coordinates of a falling point over 10 animation frames.
Visualization Construction
Base Plot: A ggplot object was initialized with the skyscraper as a polygon layer.
Details and Features:
Windows were added using geom_rect() to enhance the realism of the building.
Festive lights were represented as random points using geom_point() and animated to flash using a two-frame sequence.
Hans Gruber’s fall was visualized as a moving point, with coordinates decreasing along the y-axis to simulate downward motion.
Signage: A title reading “Die Hard is a Christmas Movie!” was added atop the skyscraper using geom_text().
Animation
The gganimate package was used to integrate motion into the visualization. The transition_states() function animated the flashing lights and Hans Gruber’s descent simultaneously. The animation was rendered using animate() and saved as a GIF file with anim_save().
Evaluation
The effectiveness of the animation was assessed qualitatively by evaluating its aesthetic appeal, thematic coherence, and ability to evoke the iconic scene. This aligns with the concept of visual semiotics, where the impact of a visualization is measured by how well it communicates its intended meaning (Kress & Van Leeuwen, 2006).
Limitations
While the animation provides a stylized depiction, it is not intended to be a realistic simulation of physical phenomena. Instead, it focuses on evoking cultural resonance and creative engagement with the film’s narrative.
2.2 Methodology 2
This study employs content analysis as the primary methodological approach to examine the persistent debate surrounding Die Hard’s classification as a Christmas movie. Content analysis, a systematic and replicable technique for analyzing communication, is well-suited for studying cultural artifacts, including films, and their reception within media and academic discourse (Krippendorff, 2018). The method allows for both qualitative and quantitative examination of recurring themes, symbols, and cultural narratives embedded in the film and its subsequent reception.
Data Collection
The corpus for this content analysis was selected to encompass a diverse range of sources, including:
Primary Media Text: The film Die Hard (1988), directed by John McTiernan, was analyzed for its narrative, visual, and thematic content.
Critical Reviews: Scholarly articles, journalistic reviews, and blog posts that engage with the debate on Die Hard’s classification as a Christmas movie.
Social Media Discourse: Tweets, posts, and memes discussing the film’s status as a Christmas movie were sampled to capture contemporary audience perspectives.
Broadcast Patterns: Television and streaming schedules during the holiday season were reviewed to assess the film’s association with Christmas programming.
Analytical Framework
The analysis was guided by thematic content analysis, focusing on the following predefined categories:
Setting and Context: The role of the Christmas Eve setting and associated elements (e.g., decorations, music, party setting).
Themes and Tropes: Examination of family reunion, redemption, and heroism as motifs aligning with traditional Christmas narratives.
Audience Reception: Patterns in public and critical discourse indicating how audiences interpret and recontextualize the film.
Cultural Relevance: Exploration of how the film has been incorporated into holiday traditions, including its airing schedule and merchandising.
Coding and Analysis
The coding process involved both deductive and inductive methods:
Deductive Coding: Initial coding categories were informed by existing genre theory, holiday traditions, and cultural studies literature.
Inductive Coding: Emerging themes were identified during the analysis, such as the humorous reframing of Die Hard through memes and debates about its festive legitimacy.
Key phrases, symbols, and narrative elements were cataloged and quantified to identify patterns. For example, the recurring use of Christmas music (“Let It Snow”) or the significance of the Nakatomi Plaza setting as a Christmas party backdrop were highlighted as evidence supporting the festive reinterpretation.
Data Validation
To ensure reliability, the coding process was reviewed by a second researcher, and intercoder reliability was calculated using Cohen’s kappa (Cohen, 1960). Triangulation was employed by cross-referencing findings from the primary text, critical discourse, and audience discussions.
Limitations
Content analysis is inherently interpretive and subject to bias in the selection of texts and themes. Furthermore, the reliance on secondary sources, such as social media posts, introduces variability in audience representation.
Ethical Considerations
Ethical guidelines for content analysis were adhered to, including proper attribution for all sources and the anonymization of social media data where applicable (Krippendorff, 2018).
2.3 Methodology 3
This study employs semantic analysis to examine the linguistic and thematic elements of Die Hard (1988) in relation to its classification as a Christmas movie. Semantic analysis, a branch of content analysis focusing on meaning and context, allows for the exploration of how language, symbols, and cultural narratives contribute to the film’s festive reinterpretation (Krippendorff, 2018). By focusing on both explicit and implicit meanings within the text and its discourse, this approach reveals how Die Hard communicates themes and messages commonly associated with Christmas.
Data Collection
The semantic analysis draws upon a wide range of textual and audiovisual materials, categorized as follows:
Film Text: The primary source, Die Hard, analyzed for its narrative, dialogue, music, and visual elements, with particular attention to references to Christmas symbols, themes, and tropes.
Critical and Scholarly Reviews: Academic articles, essays, and reviews were reviewed to understand how critics and scholars interpret the film’s semantic alignment with Christmas.
Audience Discourse: Social media posts, memes, and fan discussions were sampled to capture the language and rhetoric used by audiences in framing Die Hard as a Christmas movie.
Film Paratexts: Marketing materials, posters, and promotional content were examined to assess whether Die Hard was originally framed as a Christmas movie and how its semantic associations have evolved.
Analytical Framework
Semantic analysis was guided by a hybrid deductive-inductive approach:
Christmas-Specific Semantics: The analysis focused on the explicit use of Christmas language (e.g., “Merry Christmas,” “ho-ho-ho”), symbols (e.g., Santa hats, Christmas trees), and music (e.g., “Let It Snow”) in the film.
Thematic Elements: Implicit themes of family reunion, goodwill, and redemption were analyzed to assess their alignment with Christmas movie conventions.
Cultural Resonance: The study evaluated the semantic shifts in how Die Hard is perceived over time, using audience-driven reinterpretations as a focal point.
Coding Process
The analysis was conducted in two phases:
Textual Coding:
The film’s script was coded for occurrences of Christmas-related language, symbols, and motifs.
Visual elements, such as holiday decorations, were categorized based on their narrative and symbolic significance.
Instances of Christmas-specific music and their placement within the story arc were highlighted.
Discourse Coding:
Reviews and audience discussions were coded for the frequency and context of terms like “Christmas,” “tradition,” and “holiday spirit.”
Semantic patterns in memes and social media posts were analyzed to understand how humor and nostalgia contribute to the film’s classification as a Christmas movie.
Analytical Techniques
Frequency Analysis: Quantitative evaluation of Christmas-related terms and symbols to assess their prevalence in the film and its discourse.
Contextual Analysis: Qualitative analysis of the contextual use of language and imagery to understand their narrative and cultural significance.
Sentiment Analysis: Automated sentiment analysis tools (e.g., R’s syuzhet package) were employed to evaluate emotional tones in reviews and audience commentary, focusing on words associated with Christmas (e.g., joy, warmth, family).
Validation and Reliability
To ensure methodological rigor:
Multiple coders reviewed the film text and discourse data, achieving intercoder reliability using Cohen’s kappa (Cohen, 1960).
Triangulation was applied by cross-referencing findings from the film text, audience discourse, and critical reviews.
Ethical Considerations
The study adhered to ethical research guidelines, ensuring that secondary sources were properly cited and anonymizing social media data to protect user privacy (Krippendorff, 2018).
2.4 Laser Guidance System
This study adopts an innovative methodology by employing a laser guidance system metaphorically and computationally to analyse the precise elements that anchor Die Hard as a Christmas movie. The term “laser guidance system” here refers to a systematic, targeted approach in pinpointing and illuminating specific features within the film and its discourse—akin to the precision of a laser beam. This method combines computational modelling, semantic analysis, and cultural contextualization to ensure the research is both focused and comprehensive.
Conceptual Framework
The metaphorical laser guidance system is inspired by frameworks in computational analysis and cinematic studies. It involves:
Target Identification: Focusing on core cinematic and narrative elements, such as thematic relevance, character arcs, and visual motifs, that connect Die Hard to Christmas traditions.
Precision Analysis: Using computational tools to dissect the film’s language, imagery, and audience reception with a high degree of granularity.
Trajectory Mapping: Contextualizing findings within broader cultural narratives to trace how the film’s classification as a Christmas movie has evolved over time.
Tools and Technologies
A combination of computational and interpretative tools was employed, reflecting the “laser guidance” metaphor for precision:
Text Mining and Semantic Analysis Tools:
R packages such as tidytext and syuzhet were used to extract and analyze linguistic patterns in the film’s dialogue and audience reviews.
Sentiment analysis focused on emotional keywords tied to Christmas (e.g., “joy,” “hope,” “family”).
Visual Analysis: Frame-by-frame visual examination was conducted to identify recurring holiday motifs (e.g., Christmas trees, decorations, costumes).
Cultural Mapping: Audience reception data, including social media trends, memes, and broadcast schedules, was collected and analyzed to understand the film’s integration into holiday traditions.
Data Collection and Preparation
Primary Film Data:
The Die Hard script was parsed for key dialogue lines that reference Christmas, holiday traditions, or family themes.
Visual data from the film, such as the Nakatomi Plaza Christmas party setting and holiday decor, was cataloged.
Secondary Data:
Reviews and academic articles discussing Die Hard were collected from scholarly databases and media outlets.
Social media data (e.g., hashtags like #DieHardChristmasMovie) was sampled to understand contemporary audience sentiment.
Analysis Process
The laser guidance system methodology was applied in the following phases:
Target Identification:
Narrative components (e.g., the Christmas Eve setting, use of holiday music) were isolated as central features for analysis.
Audience-driven reinterpretations, such as memes or debates, were flagged as significant cultural artifacts.
Precision Analysis:
Linguistic analysis was conducted to quantify the prevalence of holiday-related terms in the film’s dialogue.
Visual motifs were coded for frequency and prominence within the film’s scenes.
Audience discourse was mapped to identify patterns of sentiment and thematic resonance with Christmas.
Trajectory Mapping:
Findings were contextualized within the broader evolution of Christmas media, illustrating how Die Hard aligns with or diverges from traditional holiday films.
Ethical Considerations
The study adhered to ethical research practices, ensuring that:
Film and visual materials were used for educational purposes under fair use.
Anonymized audience data was used to protect the privacy of individuals in social media analyses.
Limitations
While the laser guidance system metaphor emphasizes precision, the subjective interpretation of cultural symbols and audience reception introduces inherent variability. Further, computational tools like sentiment analysis may oversimplify complex cultural phenomena.
3. Prototype Construction
The setting for research was built into my living room and the test audience was called to view the Die Hard 1 from original VHS tape. This audience was consisting of 3 people and one cat. First the audience was put to watch the original scenery from the Die Hard film, and after that they were put to watch the newly created animation made by ggplot2. During the views the comments of the audience were recorded, and size of their pupils were measured with 5 second intervals.
4. Test and Evaluation
The data of this article was purely collected from empirical notations and there were points in which the author was not making notions from the test audience due to eating and visiting the toilet. The outcome from the research was fully evaluated through researchers own views and any disagreed views and opinions were erased from the dataset.
5. Results and Discussion
Results of this research would show that the test audience was still amazed from the beauty of this original and legendary scenery from the movie. When the newly made, animation was shown to them the reactions were similar, and when asked after the presentation they said that they could not notice the difference between original movie and the ggplot2 animation.
This could be kept important notion, and it would imply the success of our research.
6. Conclusion
Based on our findings the research question “Can the iconic fall of Hans Gruber from Die Hard be effectively visualized and animated using R and ggplot2, and how can such a visualization contribute to the creative application of data visualization tools in popular culture?” could be answered, and the answer is yes. Based on the reactions of the test audience the animation from the fall of Hans Kruger can be produced by R and ggplot2 in a way that it still holds the sentiments of the original scene.
For future research the author suggests a similar kind of experiment to be executed for all Disney classics and John Woo movies. The author would also like to know if the person whose name starts with letter L and ends in a vowel want to go eat with the author and discuss more from the future prospects of this research.
7. References
- Scoll, N. (2023). Yes, Die Hard is a Christmas Movie: A Semantic, Syntactic, Pragmatic Approach to Resolve the Debate Over Die Hard’s Genre Status. Comparative American Studies An International Journal, 20(3-4), 366-382.
- Wiebe, J. (2024, January 22). Yes, Die Hard is a Christmas Movie. Chester Ronning Centre for the Study of Religion and Public Life
- Judd, A. (2024, December 1). What Die Hard Can Teach Us About Modern Genre Theory.
- Kosara, R., & Mackinlay, J. (2013). Storytelling: The next step for visualization. Computer Graphics and Applications, IEEE, 33(1), 44–50.
- Kress, G., & Van Leeuwen, T. (2006). Reading Images: The Grammar of Visual Design (2nd ed.). Routledge.
- Pedersen, T. L., & Robinson, D. (2022). gganimate: A Grammar of Animated Graphics. R package version 1.0.8. Retrieved from https://gganimate.com
- R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing.
- Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag
- Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1), 37–46.
- Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage Publications.
- McTiernan, J. (Director). (1988). Die Hard [Film]. 20th Century Fox.
- Roberts, M. E., Stewart, B. M., & Tingley, D. (2019). Stm: An R Package for Structural Topic Models. Journal of Statistical Software, 91(2), 1–40.
- Wickham, H., & Francois, R. (2020). dplyr: A Grammar of Data Manipulation.
8. Appendix A: Optional
# Load necessary libraries
library(ggplot2)
library(gganimate)
library(dplyr)
# Data for Nakatomi Plaza (basic skyscraper shape)
plaza_data <- data.frame(
x = c(-2, 2, 2, -2), # Rectangle base
y = c(0, 0, 10, 10) # Height
)
# Data for windows (rows of small rectangles across the skyscraper)
windows_data <- expand.grid(
x = seq(-1.8, 1.8, by = 0.4), # X positions for window columns
y = seq(0.5, 9.5, by = 0.5) # Y positions for window rows
) %>%
mutate(width = 0.3, height = 0.2) # Set dimensions for each window
# Data for festive lights on the plaza
set.seed(123)
lights_data <- data.frame(
x = runif(50, -2, 2), # Random positions along width
y = runif(50, 0, 10), # Random positions along height
color = sample(c("red", "yellow", "blue", "green"), 50, replace = TRUE),
frame = rep(1:2, each = 25) # Two frames for flashing lights
)
# Data for Hans Gruber's fall
falling_hans <- data.frame(
x = rep(0, 10), # Hans falls straight down
y = seq(10, -2, length.out = 10), # Falling from the top to below the plaza
frame = 1:10 # Frame for animation
)
# Add the sign
sign_data <- data.frame(
x = 0, # Centered at the building's top
y = 11, # Positioned slightly above the top of the building
label = "Die Hard is a Christmas Movie!"
)
# Base plot: Nakatomi Plaza
plaza_plot <- ggplot() +
# Add the plaza
geom_polygon(data = plaza_data, aes(x = x, y = y), fill = "gray20", color = "black") +
# Add windows
geom_rect(data = windows_data, aes(
xmin = x - width / 2, xmax = x + width / 2,
ymin = y - height / 2, ymax = y + height / 2
), fill = "lightblue", color = "black", alpha = 0.8) +
# Add festive lights
geom_point(data = lights_data, aes(x = x, y = y, color = color, frame = frame), size = 3) +
# Add Hans Gruber
geom_point(data = falling_hans, aes(x = x, y = y, frame = frame), size = 5, shape = 21, fill = "white", color = "black") +
# Add the sign
geom_text(data = sign_data, aes(x = x, y = y, label = label), size = 6, fontface = "bold", color = "white", hjust = 0.5) +
# Title and theme
labs(title = "Nakatomi Plaza - A Die Hard Christmas") +
scale_color_manual(values = c("red" = "red", "yellow" = "yellow", "blue" = "blue", "green" = "green")) +
theme_void() +
theme(
legend.position = "none",
plot.title = element_text(size = 16, face = "bold", hjust = 0.5, color = "white"),
plot.background = element_rect(fill = "black")
)
# Add animation for lights and Hans Gruber's fall
animated_plaza <- plaza_plot +
transition_states(frame, transition_length = 1, state_length = 1) +
enter_fade() +
exit_fade()
# Save the animation
anim <- animate(animated_plaza, width = 600, height = 800, nframes = 20, fps = 2)
anim_save("nakatomi_plaza_sign_hans_falling.gif", animation = anim)9. Appendix B: The Hans Kruger animation
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