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"Social change in motion pictures."
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Desintegración y justicia en el cine argentino contemporáneo
Este libro analiza, en una serie de películas argentinas contemporáneas (Buenos Aires viceversa, 76 89 03, Nueve reinas, El hijo de la novia, Herencia y El juego de la silla), las interpretaciones y representaciones de la experiencia social de pérdida y desintegración nacional producida por la implementación de la globalización neoliberal en los años noventa en Argentina. El libro propone que estas películas articulan dos narrativas sociales centrales en la conceptualización de esa experiencia: la desintegración nacional es representada o bien como la cara oculta del espejismo massmediático de una Argentina próspera y global, resultado del proceso de transformaciones iniciado y activamente determinado por la última dictadura militar, o bien como consecuencia de una estafa perpetrada por el Estado contra una sociedad \"inocente,\" seducida por la promesa de la entrada de Argentina al \"primer mundo.\" Asimismo, estas películas dan cuenta de la desintegración de ciertas narrativas de identidad nacional, centradas en la imagen de Argentina como tierra de oportunidades y progreso y como enclave europeo en Latinoamérica. Frente a la desintegración que representan, estas películas, en su mayoría, construyen fantasías de reparación y justicia e imaginan modelos alternativos de reconstrucción comunitaria que, paradójicamente, funcionan también como modelos de reintegración nacional. GABRIELA COPERTARI es profesora en la Universidad de Case Western Reserve.
eBook
Late Westerns : the persistence of a genre
\"Mitchell argues that the Western continues to engage us because recent films deliberately defy classic patterns yet still appeal to an implicit fondness for genre conventions. Narrative expectations are so deeply stamped on our consciousness that we cannot escape reimposing assumptions on materials that barely resemble the classic Western\" -- Provided by publisher.
Book
Hot streaks in artistic, cultural, and scientific careers
The hot streak—loosely defined as ‘winning begets more winnings’—highlights a specific period during which an individual’s performance is substantially better than his or her typical performance. Although hot streaks have been widely debated in sports
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, gambling
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and financial markets
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over the past several decades, little is known about whether they apply to individual careers. Here, building on rich literature on the lifecycle of creativity
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, we collected large-scale career histories of individual artists, film directors and scientists, tracing the artworks, films and scientific publications they produced. We find that, across all three domains, hit works within a career show a high degree of temporal regularity, with each career being characterized by bursts of high-impact works occurring in sequence. We demonstrate that these observations can be explained by a simple hot-streak model, allowing us to probe quantitatively the hot streak phenomenon governing individual careers. We find this phenomemon to be remarkably universal across diverse domains: hot streaks are ubiquitous yet usually unique across different careers. The hot streak emerges randomly within an individual’s sequence of works, is temporally localized, and is not associated with any detectable change in productivity. We show that, because works produced during hot streaks garner substantially more impact, the uncovered hot streaks fundamentally drive the collective impact of an individual, and ignoring this leads us to systematically overestimate or underestimate the future impact of a career. These results not only deepen our quantitative understanding of patterns that govern individual ingenuity and success, but also may have implications for identifying and nurturing individuals whose work will have lasting impact.
The career trajectories of around 30,000 artists, film directors and scientists show that individuals in each domain have ‘hot streaks’ during which their works have increased impact, despite showing no increase in productivity.
Journal Article
Broken narratives : post-Cold War history and identity in Europe and East Asia
\"The end of the Cold War reshuffled the power relations between former friends and enemies. In Broken Narratives the contributors offer an account of the consequences of the end of the Cold War for the (re-)telling of history in film, literature and academic historiography in Europe and East Asia. Despite the post-modern claim that there is no need for a master-narrative, the contributions to this book show that we are in the middle of an intense and difficult search for a common understanding of the past. However, instead of common narratives, polyphony and dissonances are produced which reflect a world in a period of transition. As the contributions to this volume show, the year 1989 has generated broken narratives. Contributors include: Peter Verstraten, Rotem Kowner, Susanne Weigelin-Schwiedrzik, Carsten Schèafer, Martin Gieselmann, Yonson Ahn, Chang Lung-chih, Andrea Riemenschnitter, Shingo Minamizuka, Petra Buchholz, and Tatiana Zhurzhenko\"--Provided by publisher.
Book
Controlling for openness in the male-dominated collaborative networks of the global film industry
Studies of gender inequality in film industries have noted the persistence of male domination in creative roles (usually defined as director, producer, writer) and the slow pace of reform. Typical policy remedies are premised on aggregate counts of women as a proportion of overall industry participation. Network science offers an alternative way of identifying and proposing change mechanisms, as it puts emphasis on relationships instead of individuals. Preliminary work on applying network analysis to understand inequality in the film industry has been undertaken. However, in this study we offer a comprehensive approach that enables us to not only understand what inequality in the film industry looks like through the lens of network science but also how we can attempt to address this issue. We offer a data-driven simulation framework that investigates various what-if scenarios when it comes to network evolution. We then assess each of these scenarios with respect to its potential to address gender inequality in the film industry. As suggested by previous studies, inequality is exacerbated when industry networks are most closed. We review evidence from three different national film industries on network relationships in creative teams and identify a high proportion of men who only work with other men. In response to this observation, we test several mechanisms through which industry structures may generate higher levels of openness. Our results reveal that the most critical factor for improving network openness is not simply the statistical improvement of the number of women in a network, nor the removal of men who do not work with women. The most likely behavioural changes to a network will involve the production of connections between women and powerful men.
Journal Article
European cinema in motion : migrant and diasporic film in contemporary Europe
This collection brings together international experts on the cinema of migration and diaspora in postcolonial and postnational Europe. It offers a comprehensive theoretical and analytical discussion of a highly productive creative sector and documents the spectrum of this area of exploration in European, transnational and World Cinema studies.
eBook
The box office prediction model based on the optimized XGBoost algorithm in the context of film marketing and distribution
To improve the accuracy and efficiency of box office prediction, this study deeply discusses the application of the optimized eXtreme Gradient Boosting (XGBoost) model in this scenario and its advantages compared with other commonly used machine learning models. By comparing and analyzing five models, involving the Deep Neural Network, Light Gradient Boosting Machine, Random Forest, Gradient Boosting Decision Tree, and CatBoost, several key performance indicators such as accuracy, precision, recall, F1 score, generalization error, stability, robustness, and adaptability score are comprehensively investigated. The research results reveal that the optimization model proposed in this study is superior to the comparison model in most evaluation indicators, especially when the data volume reaches 2500, showing obvious advantages. For example, the accuracy is increased to 0.9, the F1 score is 0.9, the generalization error is reduced to 0.09, and the stability score is as high as 0.98. The robustness and adaptability scores are both 0.97, which proves its strong prediction ability and high stability and robustness on large-scale datasets. Therefore, this study provides scientific data support and a decision-making basis for the film industry in the formulation of marketing and distribution strategies. Moreover, film producers and distributors can reasonably estimate their market performance early in film shooting, optimize investment decisions, and reduce economic risks through accurate box office predictions.
Journal Article
Analysis of top box office film poster marketing scheme based on data mining and deep learning in the context of film marketing
With the development of science and technology and the continuous changes of social environment, the development prospect of traditional cinema is worrying. This work aims to improve the publicity effect of movie posters and optimize the marketing efficiency of movie posters and promote the development of film and television industry. First, the design concept of high grossing movie posters is discussed. Then, the concept of movie poster analysis based on Deep Learning (DL) technology is analyzed under Big Data Technology. Finally, a movie poster analysis model is designed based on Convolutional Neural Network (CNN) technology under DL and is evaluated. The results demonstrate that the learning curve of the CNN model reported here is the best in the evaluation of model performance in movie poster analysis. Besides, the learning rate of the model is basically stable when the number of iterations is about 500. The final loss value is around 0.5. Meanwhile, the accuracy rate of the model is also stable at the number of iterations of about 500, and the accuracy rate of the model is around 0.9. In addition, the recognition accuracy of the model designed here in movie poster classification recognition is generally between 60% and 85% in performing theme, style, composition, color scheme, set, and product recognition of movie posters. Moreover, the evaluation of the model in the movie poster style composition suggests that the style composition of movie poster production dramatically varies in different films, in which movie posters focus most on movie product, style, and theme. Compared with other models, the performance of this model is more outstanding in all aspects, which shows that this work has achieved a great technical breakthrough. This work provides a reference for the optimization of the design method of movie posters and contributes to the development of the movie industry.
Journal Article
American Cinema of the 2010s
The 2010s might be remembered as a time of increased polarization in American life. The decade contained both the Obama era and the Trump era, and as the nation’s political fissures widened, so did the gap between the haves and have-nots. Hollywood reflected these divisions, choosing to concentrate on big franchise blockbusters at the expense of mid-budget films, while new players like Netflix and Amazon offered fresh opportunities for low-budget and independent filmmakers. As the movie business changed, films ranging from American Sniper to Get Out found ways to speak to the concerns of a divided nation. The newest installment in the Screen Decades series, American Cinema in the 2010s takes a close look at the memorable movies, visionary filmmakers, and behind-the-scenes drama that made this decade such an exciting time to be a moviegoer. Each chapter offers an in-depth examination of a specific year, covering a wide variety of films, from blockbuster superhero movies like Black Panther and animated films like Frozen to smaller-budget biopics like I, Tonya and horror films like Hereditary. This volume introduces readers to a decade in which established auteurs like Quentin Tarantino were joined by an exceptionally diverse set of new talents, taking American cinema in new directions.
eBook