Movie Production Research Articles

Movie Success Prediction Based on Feature and Trailer Comments Using Ensemble+LSTM Model

Predicting the success of a movie is a very important aspect due to the high risks involved in movie production. The challenge lies in the uncertainty within the movie industry and selecting the appropriate machine learning model. We can combine movie features and sentiment analysis from social media using machine learning techniques to achieve movie success prediction. The methods used for predicting based on movie features are Ensemble models (Random Forest + Gradient Boosting). Meanwhile, the methods used for sentiment analysis of trailer comments is LSTM. The evaluation of the models used is based on RMSE and accuracy calculation. The final prediction of success obtains an RMSE of 0,8807 and an accuracy of 91,19%. This represents an improvement from previous research. Further research is recommended to implement the model in the movie industry

The Image of the US Army in American movies: The Soft Power of American Cinema

The formation of the army's image has acquired newfound significance in our time. Paradoxically, alongside the spread of humanist ideology, the number of violent conflicts worldwide is increasing. These stimulates the need for propaganda aimed at shaping the image of the army and enhancing the attractiveness of service. As one of the world's largest military forces, the US army has engaged in a diverse array of conflicts with over 750 military bases in approximately 80 countries (Kohli 2020). A diverse range of tools is employed to shape the image of the US army, including media, recruitment campaigns, social media, public events, etc. Among these tools, movies have their specific role. While traditionally intended for entertainment, movies have been used for over a century as a means to shape public opinion. This article delves into the main attributes of the US Army as a social institution, analyzing its four fundamental characteristics: the Militia Tradition, Mobilization Miracles, Man-Mindedness, Maritime Influence, the weapon and the enemy as distinctive attributes. Additionally, it features the seven core values of the US Army: Loyalty, Duty, Respect, Selfless Service, Honor, Integrity, and Personal Courage. The article provides a detailed analysis of how various components of movie production tools communicate the attributes and core values of the US Army and contribute to shaping its image, examining a high-viewership movie “Interceptor” (2022). The goal of the study was to find out the image of the US Army that “Interceptor” projects and to identify the verbal and visual communicative means it uses for this purpose. The content analysis made it possible to distinguish verbal and visual elements of the movie, encompassing human voice, mise-en-scène, as well as film editing techniques, to identify and highlight the messages and ideas conveyed about the attributes of the US Army.

Research on the Impact of Social Media Marketing of Films on Consumer Behaviour

Before and at the early stage of a movies release, a successful movie marketing strategy will have a great attraction and influence on the target audience. The trailer is a marketing tool used before the official release of a movie, and its main function is to market and publicize the movie to a general audience, as well as be an effective tool for the audience to understand the movie. And topic marketing is to position the content of the movie through emotional value, social topics, potential consumer experiences, and so on, to build consumer awareness of the movie. Effective marketing promotion can increase the conversion rate of the audience want to see by influencing consumer decision-making behavior. Therefore, this paper explores the impact of two social media marketing methods (trailer marketing and topic marketing) on consumer decision-making behavior on Weibo and Douyin from the perspective of the audiences want to see conversion rate. This will provide a useful reference for movie producers to carry out effective marketing promotions.

WILL AI REPLACE HUMAN JOBS IN THE FILM PRODUCTION?

Artificial Intelligence is utilized in multiple steps of film production such as script writing, Pre-production works, identifying locations, casting the actors, calculating the budget of the film, Box-office performance, Demographics of the audience, enhancing VFX, animations, CGI, music and Post-production works (Editing, colouring, sound design). This article explores the arrival of AI in film production, popular filmmaker’s and artists’ opinions on AI, how AI benefits and challenges human jobs in the Film industry, and AI which are used in every stage of filmmaking. This article elucidates about movies generated through AI, how popular movie production companies like 20th Century Fox, and Warner Bros. use AI as a tool to enhance their films, AI which are used to generate films, and jobs that AI is unlikely to replace. This article concludes by stating how humans should use AI in order to sustain in this era of AI.

Mining Chinese Animation Movie Audience Concern Themes Based on BERTopic and UGC

[Objective] To explore how Chinese animated movies can effectively utilize hot topics to feed the box office and improve the competitiveness of the movies by mining hot topics of users' concern through User-Generated Content (UGC). [Methods] Based on the UGC text of Douban reviews of the Chinese animated movie "30,000 Leagues in Chang'an", we adopt the BERTopic algorithm to cluster topics based on the category-based TF-IDF (Word Frequency-Inverse Text Frequency)-weighted clustering, and introduce the semantic fine-tuning of the topics by the ChatGLM2-6B model to excavate the hot topics of users' attention. [Results] Users of the Chinese animated movie "30,000 Leagues in Chang'an" pay attention to five major topic clusters, including Chinese culture, word-of-mouth communication, poetic narrative, production technology, and the controversy of new historical facts. [Limitations] The country differences in the topic concerns of Chinese animated films were not analyzed in comparison with foreign UGC texts. [Conclusion] This study focuses on UGC text analysis to discover the social attention and evolution law of related topics. These findings provide some reference value for future Chinese animated movie production and production, box office prediction and marketing.

A refined approach to early movie box office prediction leveraging ensemble learning and feature encoding

Predicting the revenue of a movie prior to its release presents a significant challenge. The ability to predict pre-release revenue enables movie production companies to devise effective marketing strategies and mitigate the risks associated with potential box office failures. The primary hurdles in this endeavor stem from managing the myriad factors influencing box office outcomes and accurately forecasting a movie's revenue before it becomes available to the public. To overcome these challenges, we introduce a sophisticated Early Movie Box Office Prediction Model that incorporates Ensemble Learning and Feature Encoding techniques. This model amalgamates multiple foundational models, utilizing regression and decision trees to forecast box office revenues. Our composite model demonstrates superior performance over its constituent models, achieving an impressive accuracy rate of 91.4%.

Video Detection Method Based on Temporal and Spatial Foundations for Accurate Verification of Authenticity

With the rapid development of deepfake technology, it is finding applications in virtual movie production and entertainment. However, its potential for malicious use, such as generating false information, fake news, or synthetic pornography, poses significant threats to national and social security. Various research disciplines are actively engaged in developing deepfake video detection technologies to mitigate the risks associated with malicious deepfake content. Therefore, the importance of deepfake video detection technology cannot be overemphasized. This study addresses the challenge posed by images in nonexistent datasets by analyzing deepfake video detection methods. Using temporal and spatial detection techniques and employing 68 facial landmarks for alignment and feature extraction, this research integrates the attention-guided data augmentation (AGDA) strategy to enhance generalization capabilities. The detection performance is evaluated on four datasets: UADFV, FaceForensics++, Celeb-DF, and DFDC, with superior results compared to alternative approaches. To evaluate the study’s ability to accurately discriminate authenticity, detection experiments are conducted on both genuine and deepfake videos synthesized using the DeepFaceLab and FakeApp frameworks. The experimental results show better performance in detecting deepfake videos than other methods compared.

Geoheritage and Geoconservation, from Theory to Practice: The Ghost Town of Craco (Matera District, Basilicata Region, Southern Italy)

Several theoretical and applied studies are concerned with the topics of geological heritage management and geoconservation. The diversity of natural and anthropic scenarios into which geological heritage is inserted, as well as its troublesome management, make these topics challenging for scientific discussion. However, on the other hand, these topics highlight the complexity of a theoretical schematization of approaches and procedures, as well as of the practical application of theoretical assumptions. This paper concerns a practical application of a case study in geoconservation actions, which begins with the identification and the basic description of a site of multicultural interest (characterized by the coexistence of geo and non-geo aspects); subsequently, the needs and aims of the potential end users and stakeholders are analyzed. Finally, several geoconservation actions, differentiated according to end user and stakeholder goals, are proposed. The chosen area includes the Craco ghost town in southern Italy. It is a characteristic, evocative place, where it is possible to observe natural and anthropic contexts. The Craco ghost town is also nationally and internationally renowned, since some movie productions have been set there (such as some scenes in Mel Gibson’s The Passion of Christ movie). In this area, the abBandono vErsus riGenerazIoNe (BEGIN) Project (ROP ERDF Basilicata 2014–2020 interregional and transnational cooperation projects) aims to develop an operative, unequivocal, and multi-layered procedure focused on sustainable management, disseminating knowledge and enhancing and using the cultural context of abandoned sites as an attractive force for tourist purposes.

Cross-platform adaptation of algorithmic editing techniques

The research relevance is determined by the rapid development of technology and the growing need for efficient data processing on various platforms. The study aimed to address methods that would enable the use of data editing algorithms on various operating systems and hardware platforms. A methodology was developed for studying cross-platform adaptation technologies, including cross-compilation, virtualisation, the use of universal libraries and Application Programming Interface, as well as methods for testing and optimising algorithm performance. The study addressed various approaches to implementing cross-platform compatibility, including the use of cross-compilation, virtualisation and containerisation. The main technical challenges are managing resources, optimising performance and ensuring compatibility with hardware from different platforms. The principles included selecting the most appropriate technology for the task at hand, considering performance and security requirements, and ensuring effective integration of existing systems and infrastructure. The workflows are focused on creating modular and extensible solutions that can easily adapt to changes in the technological environment and user requirements. In the context of this study, artificial intelligence software plays a key role in improving the efficiency and accuracy of data processing across different platforms. The results showed that artificial intelligence software can automate various stages of the video and audio editing process. Artificial intelligence is used to analyse large amounts of content data, such as video files, images and audio recordings. The study determined that artificial intelligence is increasingly relevant in various aspects of movie production. Artificial intelligence can analyse scripts, predict their potential success and suggest improvements using data from previous films and their commercial success

Analysing the Character Types and Power Relationships in Metaverse-Themed Movies from the Perspective of Discipline and Anti-discipline

ABSTRACT Since the end of 2021, the concept of “metaverse” has received widespread attention in academic field. Movie sector has long been exploring it prospectively and presenting it innovatively, resulting in the production of metaverse-themed movies. This type of movie has practical significance for the future metaverse thesis. “Character” is an important narrative sign of film composition. This paper starts with several meta-cosmic films, divides the types of characters in meta-cosmic films according to Foucault's theory of spatial power, and analyses their prototype indexes and formation reasons from the constitutive factors of the power relationship, thus explores the power relationship of various types of characters in the metaverse-themed films.

Sentiment analysis and implementation in film evaluation utilizing BERT

This study explores the use of the dmsc_v2 dataset, which is a rich collection of over 2 million ratings and commentary data from over 700,000 users on 28 films, to train the BERT model for sentiment analysis. This expansive dataset, drawn from the popular Chinese movie-rating website, Douban, has been meticulously curated for this research. In the context of the methodology, it is comprehensive and involves multiple stages. Initially, data preprocessing is conducted to refine and format the dataset suitably for model training. Subsequently, the BERT model is trained using the prepared data. Following the training process, the model's performance is critically evaluated to validate its efficacy and accuracy. The resulting model is adept at performing sentiment classification on comments pertaining to films across various social media platforms such as Weibo, Xiaohongshu, and more. This is particularly beneficial as it enables a nuanced analysis of user opinions and trending topics, offering invaluable insights for businesses, movie producers, or marketers. The findings of this study demonstrate that the BERT sentiment analysis model, developed with the dmsc_v2 dataset, exhibits impressive performance and has expansive potential for application within the sphere of social media commentary analysis. The successful development and validation of this model underscore its potential to transform the way sentiment analysis is conducted, especially in the context of entertainment and social media discussions.

Marvel Movies: Film Manufacturing in the Digital Agecomic

As technology continues to develop and innovate, the movie manufacturing industry is also evolving. Through the use of digital technology, film production has become more efficient, precise and realistic. Movie production, because of technological innovations should develop a new vitality. This thesis will explore how technological innovation has helped movie manufacturing and the application of digital technology in Marvel movies. Firstly, this paper will introduce the concept and development history of special effects in film and television, including traditional special effects techniques in film and television and special effects techniques in the digital era. Then, this paper will focus on the application of digital technology in Marvel movies, including the application of technology in artificial intelligence, special effects technology and marketing and promotion. Finally, this paper will summarize the impact of technological innovation on film manufacturing and look forward to future trends.

Analysis of the New Mode of Movie Marketing Communication --The Example of the "TikTok-style Movie"

This paper introduces the concept of "TikTok-style Movie" and illustrates a new marketing and communication model jointly constructed by movie producers, new media organizations or KOLs, and the general public under the influence of the short-video communication method of the platform "TikTok". By analyzing the impact of TikTok marketing on the content, shooting, and editing of the film production itself through the context of practical case studies to peek into the direction of the development of film production; exploring the advantages and disadvantages of the movie market brought by the emergence and expansion of "TikTok-style Movie". At the same time, analyze the path to success of the advantages and how to overcome the shortcomings, improve the TikTok marketing and improve the quality of the films. This paper will also explore the future of the "TikTok-style Movie" and the development direction of Chinese movies in terms of movie content, marketing methods, platform cooperation, and other aspects.

Discovering the relationship between the number of film review topics and box office with NLP techniques

Numerous movie reviews on the internet can be used to analyze audience experiences of movies and provide inspiration for the operation and production of movies. In this work, we integrate and match the review data on Douban and the box office data on the website maoyan.www, and utilize the topic model in natural language processing to determine the number of each movie review topics, then establish an regression equation to analyze the relationship between the number of topics and movie box office. Our analysis shows a significant positive correlation between film box office and the number of movie review topics, and we have provided an explanation for this. Finally, we also analyzed the practical application value of this work.

The Use of Digital Media Arts in Animation Filmmaking in the Age of Digital Intelligence

Abstract The development of digital media art has brought a broader application prospect for the production of digital animation movies. The incorporation of Digital Media Arts into Animation Filmmaking during the Age of Digital Intelligence The DTW algorithm is selected to temporally regularize and align the motion data of the animated character, and the motion model is downsized and optimized by combining with the PCA method, to obtain the motion sequence with the characteristics of the animated character itself. The multi-scale method is utilized to decompose the original motion data when combined with motion capture technology to establish a 3D motion database. Analyze the motion connection curves between different video clips and the generated animation data after and before motion modeling using the 3D motion database of broadcast gymnastics. Analyzing the drawing efficiency of virtual character models is done using an ordinary human character model with different voxel accuracy. Before the motion library modeling, the average joint error measured in degrees was 10.012°, as indicated by the data. The modeling procedure results in a reduction of the average joint error to 4.281°. The accuracy of animated character generation motion can be improved by using motion modeling. Character motion generation suggestions for animated movie production are provided in this study.

Covid-19: National Lockdowns and Social Distancing Exposes Gender Inequalities in the Market Places of Zimbabwe

The day the earth stood still! This is a title of a western movie production that is pregnant with meaning in as much COVID-19 is concerned. However, this was not a matter of a day as days turned to weeks and weeks turned to months. Lives have been turned upside down for the entire human race. Different economic statuses have also had both negative and positive impact on families the world over. Female breadwinners are facing difficulties in trying to look after families during this COVID-19 environment. The African continent found itself on the receiving end and had to systematically respond to this global pandemic through the announcements of closing borders and lockdowns in a bid to combat the spread of the deadly virus. Several gender policies and instruments have been put in place to create gender responsive environments. It is while implementing these measures that the Zimbabwean societies have realised that the female bread winners are on the losing side as most of their activities are directly affected by the se covid-19 safety measures. It is on this background that this paper is underpinned to demonstrate the vulnerability of the females on the market places. The study which is informed by qualitative research, made use of document analysis. In addition deep structured interviews with female breadwinners. Due to social distancing measures all interviews were conducted online. The paper also put in place recommendations that can be implemented during and after covid-19 period, so that there is gender equity in the market places.

Research and Innovation of Animated Movie Production Technology Based on Computer Graphic Design

Abstract The animation technology of computer graphic design can creatively integrate artificial intelligence technology and animation art, and use artificial intelligence technology to realize the creation of animation with the support of computer graphics. Based on this, this paper constructs a particle special effects system to realize the innovation of animation film production technology. This paper first analyzes the functions that need to be realized by the system and carries out the overall design of the system framework using modeling language. This includes the detailed design and graphical representation of the particle module, scene module, texture module, and so on in the particle special effects system. Then, simplify the mathematical model of snow, rain, fountain, etc., establish the particle system model of snow, rain and fountain, and realize the special effects simulation of snow, rain, fountain and other landscapes. Through the experiments, the performance of this system passes the standard of 70 frames per second, and the average score of the evaluation index of “whether there are common phenomena in animation” reaches 9.1 points, but the average score of the particle effects to express the emotions of the characters is only 6.3 points, which indicates that this system realizes the special effects simulation of snow, rain and fountain. This shows that the system in this paper has achieved the special effects simulation of snow, rain, and fountain phenomena, but there is still room for improvement in the expression of characters’ emotions with particle effects. On the whole, the system in this paper has achieved excellent special effects simulation and has realized the innovation of animation film production technology.

상업영화 공동제작 네트워크 내재성(Network Embeddedness)과 흥행 성과 간 역 U자형 관계 탐구

In this study, we analyze the impact of embeddedness in co-production networks within the film industry on the commercial success of movies. We aim to determine whether the success in the popular culture industry, particularly in the film industry, is attributable to the network characteristics of suppliers. To this end, drawing on insights from network theory and related prior research, we propose a set of hypotheses regarding the relationship between the structural embeddedness within the network among film production companies and their box office performance. To test these arguments, we collected detailed information on feature films shown in US box offices from IMDB, resulting in a dataset of 2,752 movies for analysis. We utilized network constraint as an indicator of network embeddedness, Employing OLS regression analysis, we confirmed an inverted U-shaped relationship between network constraint and box office revenue, as hypothesized. However, we also found that this relationship varies depending on the characteristics of the movie. In the case of movies with high artistic quality, multiple genres, or large production budgets, we observed a mitigation in the pattern of the inverted U-shaped relationship. The results of our study indicate that while network embeddedness at a moderate level provides movie production companies with ease of access to resources and information, excessive embeddedness can hinder creative diversity and innovation. Our research offers valuable insights, emphasizing the importance of maintaining balance and diversity in supplier networks for the healthy development and sustainability of the cultural and arts industry.

Explainable Neural Network analysis on Movie Success Prediction

These days movies are one of the most important part of entertainment industry and back in the days you could see everyday people standing outside theatres, or watching movies in OTT platforms. But due to busy schedules not many people are watching every movie. They go over the internet and search for top rated movies and go to theatres. And creating a successful movie is no easy job. Thus, this study helps movie producers to consider what are the important factors that influence a movie to be successful. this study applied neural network model to the IMDb dataset and then due to its complex nature in order to achieve the local explainability and global explainability for the enhanced analysis, study have used SHAP (Shapley additive explanations) to analysis.

Political behavior and voting for tax incentives

ABSTRACT This study looks at the factors which influence state legislators’ votes on movie production tax incentives. It investigates the relationship between votes cast by state legislators for/against movie production subsidies with respect to election results, political party, political donations, and district geographic and economic characteristics. Votes depend on incentives offered by neighbouring states, political affiliation, margin of election victory, and district unemployment. The number of movies filmed in the district prior to legislative action or political contributions to legislators from movie industry donors are not important vote determinants on this issue. Districts that voted for incentives appear to receive a greater increase in post-legislation film production than those that voted against legislation. Using statewide ballot initiatives to measure voter preferences, the data indicates that legislator votes on movie tax incentives reflect the underlying beliefs of their districts and is consistent with the median voter theorem.