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AbstractSmart Predict is a novel two-tablet application developed to improve conversational efficiency for people who use augmentative and alternative communication (AAC) devices. The Smart Predict system consists of two distinct applications that were built for use with two Android tablets and/or phones with Bluetooth® capability. One application is referred to as the AAC User app and the second application is called the Partner app. Smart Predict integrates vocabulary supplementation from communication partners in real-time while persons who rely on AAC generate text and maintain full control to choose words within a word prediction line. Using single-case research designs with adapted alternating treatments under two counterbalanced treatment conditions (AAC User app alone versus AAC User app + Partner app), we examined message efficiency with persons who rely on switch scanning for on-screen keyboards. User experience questionnaires were administered to determine satisfaction and workload, and to provide feedback for future development efforts. Three adults with complex communication needs and motor impairments conversed with research staff about fourteen movie trailers. Characters per minute and switch selections per character produced by the person with complex communication needs and motor impairments were measured during 15-minute interviews to represent communication speed and effort. Results indicate that message efficiency increased with the dual-tablet Smart Predict, indicating faster message generation with the vocabulary supplementation system. User satisfaction increased and perceived effort decreased under the Smart Predict conditions. Given these results within a research and development framework, the Smart Predict concept is a viable feature that could be considered within smart AAC technologies. [ABSTRACT FROM AUTHOR]

Movie genre prediction from trailers is mostly attempted in a multi-modal manner. However, the characteristics of movie trailer audio indicate that this modality alone might be highly effective in genre prediction. Movie trailer audio predominantly consists of speech and music signals in isolation or overlapping conditions. This work hypothesizes that the genre labels of movie trailers might relate to the composition of their audio component. In this regard, speech-music confidence sequences for the trailer audio are used as a feature. In addition, two other features previously proposed for discriminating speech-music are also adopted in the current task. This work proposes a time and channel Attention Convolutional Neural Network (ACNN) classifier for the genre classification task. The convolutional layers in ACNN learn the spatial relationships in the input features. The time and channel attention layers learn to focus on crucial timesteps and CNN kernel outputs, respectively. The Moviescope dataset is used to perform the experiments, and two audio-based baseline methods are employed to benchmark this work. The proposed feature set with the ACNN classifier improves the genre classification performance over the baselines. Moreover, decent generalization performance is obtained for genre prediction of movies with different cultural influences (EmoGDB). [ABSTRACT FROM AUTHOR]

The coming attraction film trailer has successfully maintained its prominent role within film promotion for over a hundred years. This article explores the shifting historical status of the trailer within the film industry and how industry trade press reported on its development and widespread adoption. Across this period these publications worked to delineate the discursive borders within which trailer debate occurred: from attacks on the trailer's usefulness to related claims of accuracy and fidelity. Exploring the creation of this discourse challenges the idea that the increasingly negative tone around the film trailer in the twenty first century is a uniquely modern phenomenon. The article argues that these initial industry strategies need to be understood in relation to key cultural and industrial concerns around commerce and artistry, critical cultural gatekeeping, and broader interests in forecasting. By focusing on a largely overlooked element of the classical Hollywood system, we demonstrate how trailers existed in a disputed space within that system: a crucial promotional tool but also a creatively potent film text. [ABSTRACT FROM AUTHOR]

Predicated upon a corpus of 4,200 films, this article documents, analyses, and interprets the international film industry's rhetorical disavowal of the comic book medium as a source for adaptation within advertising and promotional rhetoric for the cinematic adaptation of comic book texts. By analysing the statistical trends and patterns for comic book adaptations between 2000 and 2020, examining the language used within promotional trailers to conceptualise or promote the feature adaptation in relation to their comic book source material, and by comparing the type and scope of this rhetoric with other adapted texts of the same period, this article evidences and interrogates the overwhelming disavowal of the comic book medium despite the persistent and widely perceived ubiquity of comic book adaptation franchises. Above all, this article utilises statistical evidence and analysis to evidence clear patterns and trends within the perceived hierarchies of cultural taste or artistic value. [ABSTRACT FROM AUTHOR]

This paper aims to understand the antecedents of Bollywood movie success in India. This is a conceptual paper based on primary data and secondary data available from published work related to movie success. The research design employed is exploratory research design. The research paper is qualitative in nature; data collected with the help of in-depth interviews. The major antecedents are the budget of the movie, trailers of the movie, movie sequel, lead actor and actress, production house, critics' rating, IMDB ratings, tweet ratings, social media, and promotional campaign influences the success of Bollywood movies. [ABSTRACT FROM AUTHOR]

Cinematographers represent a group of experts whose professional skills depend to a great extent on their visual perceptual abilities. By the term perceptual professionalization, we emphasize the embodied dynamics of perceptual learning processes that shape the ways in which cinematographers make creative decisions during their daily practices. Novice cinematographers are initiated in film schools and during assisting jobs to a range of technical skills required for working as heads of the camera department in film productions. However, honing one's perceptual skills as a professional cinematographer is nothing less than a lifelong process. While scientific studies show evidence for behavioral and physiological differences between experts and novices in many different fields, so far no such studies exist between professional cinematographers and novices. As a starting point for studying how cinematographers' perceptual learning evolves from the level of novice to that of experienced professional, we assumed that the different expertise levels of cinematographers can be observed in the way they view moving images. We then conducted an eye-tracking case study where we identified differences in the gaze patterns between film professionals with different levels of expertise in cinematography during viewing a film trailer. As the experiential heuristics of creative decision-making of professional cinematographers largely rely on the practical skills accumulated in film work, in order to gain access to such knowledge, we also report how involving a practicing cinematographer both in designing the study and in analyzing the results provided us new insights to the topic under scrutiny. Based on our findings, a new study protocol is proposed. [ABSTRACT FROM AUTHOR]

Trailers for movies are generally considered aesthetic independent multimodal fragmented discourse. Since one of the key features of trailers for docudramas is to promote arguments in order to propagate the importance and worthiness of documentaries to be watched, trailers rely heavily on limited fragmented compositions and implicitness to arouse the viewer's curiosity. This study aims to provide an enthymematic interpretation of the trailer for Netflix's brand-new docudrama Queen Cleopatra, which has resulted in immense controversy in Egypt since its release in April 2023. Thus, the study investigates how the enthymematic property of the selected trailer is constructed through the illocutionary pluralism in the characters' argumentative polylogues and presented through the interplay of verbal-visual semiotic resources such as montage techniques, music, moving images, colors, etc. This study adopts Wildfeuer and Pollaroli's (2017) theoretical framework of multimodal argumentation in movie trailers supported by Lewiński's (2021) illocutionary pluralism in argumentative polylogues. The framework foregrounds the importance of the surrounding context (Pragma-Dialectics) in multimodal rhetoric and dwells upon two levels: logic of film discourse interpretation and argumentative reconstruction of the movie trailer. Findings have revealed that the interplay of cross-modal devices and speech acts stimulates spectators to form hypotheses and draw inferences on the cinematic discourse they are subsequently invited to watch and thus to retrieve arguments in support of the claim that the advertised documentary is worth watching. [ABSTRACT FROM AUTHOR]

Chinese subtitling of English trailers is essential for marketing foreign films in China, and there is a need to focus on audience reception. Ideal subtitles are expected to provide a necessary aid to the audience but to attract as little attention as possible. Paralinguistic factors like punctuation can influence the audience's attention and reception. Therefore, this study aims to explore the impact of punctuation on a Chinese audience's attention distribution between subtitles and visuals via the eye tracking technique. We recruited 62 participants and selected ten English trailers for films to be released. We prepared two parallel Chinese versions for each trailer, one using punctuation marks and the other using spaces. The participants were randomly assigned into two groups to watch the two versions respectively and filled out a questionnaire afterwards to rate their desire to watch those films. Data analyses show that, while punctuation does not have a significant impact on participants' attitudes towards the films, the version without punctuation causes less fixation on subtitles, implying that omitting punctuation marks can ensure more attention to the visual and hence a better viewing experience. [ABSTRACT FROM AUTHOR]

Social media listening has become an integral part of many companies marketing strategies. Using a unique dataset of social media comments to 413 movie trailers, we document the systematic differences in sentiments expressed on Facebook and YouTube. First, Facebook comments are less likely to involve sentiments. Second, when sentiments are expressed, Facebook comments tend to be more positive than those on YouTube. Third, on both platforms, comments are more likely to express sentiments after a movie's release than before it. Furthermore, the sentiment gap between Facebook and YouTube diminishes after a movie's release. We propose a behavioral explanation for our findings based on network structure and social desirability bias and test our hypothesis with an experiment. Finally, we demonstrate that cross-platform sentiment divergence is significantly associated with box office revenue. [ABSTRACT FROM AUTHOR]

Electronic word of mouth (eWOM) is one of the most influential forms of information and strongly affects customers' willingness to adopt new innovations. Using four metrics of eWOM from YouTube—the numbers of likes, dislikes, views, and comments—this study empirically investigates the dynamic relationships between eWOM and movie box office sales based on innovation diffusion theory. The results show that the innovation diffusion process is applicable in the movie industry. That is, the impacts of the number of views, likes, dislikes, and comments for movie trailers on YouTube on movie box office revenue are first increasing and then gradually decreasing. [ABSTRACT FROM AUTHOR]

On December 20, 2022, in what appears to be a first, a court determined that a studio may face legal liability for deceptive advertising for including an actress and a scene in a trailer promoting a movie, when neither was in the actual movie. Some have suggested that such an action might be barred by the First Amendment, based on the Supreme Court's suggestion in the 1983 case Bolger v. Youngs Drug Products Corp., that advertising for fully protected speech products, such as movies, may be entitled to the same level of protection as the products themselves, instead of the lower level of protection accorded to commercial speech. The Supreme Court has never made clear the limits of the applicability of this observation. Examining the cases cited by the Court to support this statement, as well as Supreme Court commercial speech cases involving protected speech since that time, this article concludes that the application of this observation should be limited to commercial speech involving religious and charitable solicitation. The Court has not given any indication that this observation should be extended to cases involving commercial speech for entertainment products. Thus, movie studios may face liability for deceptive movie trailers. [ABSTRACT FROM AUTHOR]

This article analyses the function and form of acoustic startle events (ASEs) in trailers for fifty US horror films released between 2011 and 2015. There are 173 ASEs in the sample, ranging from one startle up to a maximum of ten, with a median of three events per trailer. ASEs exhibit different types of relationships between figure and ground, with some events preceded by silence and anticipated by the viewer while others are unanticipated and intrude on scenes relying on a prior emotional state of apprehension. The functions of ASEs within the hybrid form of a trailer are emotional, narrational, aesthetic and attentional. Sound designers deploy ASEs to exploit the defensive mechanism of the startle response by using ASEs as a form of attentional redirect in order to engage the viewer with on-screen information and presenting marketing information to be remembered by the viewer during a hypervigilance phase. Startle events in the sample are typically the product of the interrelationship between sound design, editing, and movement, but there are also numerous instances when a startle event is not associated with a cut and a moment of horror is the product of the combination of an acoustic startle and movement only. [ABSTRACT FROM AUTHOR]

With the influx of online video uploads, a robust method for detecting video copies under various distortions is essential for copyright protection and search efficiency. We propose a compact video representation that uses a Siamese Neural Network for near-duplicate detection. This approach achieves up to 0.998 recall and 0.853 precision, even with distorted 56x56px miniatures. Consequently, we derive extremely compact video descriptors, facilitating video fragment retrieval in large datasets. Our method pre-selects frames from a video by identifying local maximums from the interframe differences curve, preserving characteristic sequence patterns even after extreme compression. Utilizing a simpler convolution-based model in the Siamese Neural Network, we improve results by up to 8% over VGG-16, with a 1.7-fold reduction in inference time. With compact descriptors of 1.875 kB, our models outperform others by more than two times. Additionally, we introduce a new dataset with dynamically changing scenes, enhancing its suitability for near-duplicate video detection. • Downscaling pre-selected video frames creates a sequence with a distinctive pattern. • Proposed video descriptor is robust to a wide range of modifications. • Our approach enables efficient video storage and copy detection without accuracy loss. • A diverse and dynamic video dataset was created based on movie trailers. • Created dataset shows good generalization ability for video copy detection problem. [ABSTRACT FROM AUTHOR]

We introduce a novel method for movie genre classification, capitalizing on a diverse set of readily accessible pretrained models. These models extract high-level features related to visual scenery, objects, characters, text, speech, music, and audio effects. To intelligently fuse these pretrained features, we train small classifier models with low time and memory requirements. Employing the transformer model, our approach utilizes all video and audio frames of movie trailers without performing any temporal pooling, efficiently exploiting the correspondence between all elements, as opposed to the fixed and low number of frames typically used by traditional methods. Our approach fuses features originating from different tasks and modalities, with different dimensionalities, different temporal lengths, and complex dependencies as opposed to current approaches. Our method outperforms state-of-the-art movie genre classification models in terms of precision, recall, and mean average precision (mAP). To foster future research, we make the pretrained features for the entire MovieNet dataset, along with our genre classification code and the trained models, publicly available. [Display omitted] • Pretrained features enable shallow neural networks for improved video classification. • We propose and compare novel architectures including a raw input-based baseline. • Transformers remove the limitation on the number of input video frames. • We set a new state-of-the-art for video genre classification on MovieNet. • We make available the pretrained features, our code, and trained models. [ABSTRACT FROM AUTHOR]

The multidimensional analysis (MDA) approach was brought in by Douglas Biber (1988) to compare written and spoken registers in English in the first instance, but it has comprehensively started getting applied to many different genres. The present study uses 100 texts of Hollywood movie trailers from five different genres i.e. romantic, horror, comic, animated and crime thrillers. The study aims to decipher the extent of variations found in the movie trailers pertaining to linguistic functionality. To explore the linguistic variation within movie trailers across genres, multi-dimensional analysis (MDA) is opted. Thereupon, the linguistic features used in the five genres are studied and contrasted against Biber's dimensions. The comparative study found that most of the movie trailers of designated genres go along Dimension 1 and resultantly considered as informational rather than involved as per Biber's textual dimensions. Similarly, the rest of the four dimensions collectively reveal slight variations in the selected trailers of varied genres. It can be claimed that the movie trailers are commonly created using standardized strategies and techniques without focusing on the particularities and demands of the specific genre. [ABSTRACT FROM AUTHOR]

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Consumers have an increasingly wide variety of options available to entertain themselves. This poses a challenge for content aggregators who want to effectively promote their video content online through original trailers of movies, sitcoms, and videogames. Marketers are now trying to produce much shorter video clips to promote their content on a variety of digital channels. This research is the first to propose an approach to produce such clips and to study their effectiveness, focusing on comedy movies as an application. Web-based facial-expression tracking is used to study viewers’ real-time emotional responses when watching comedy movie trailers online. These data are used to predict both viewers’ intentions to watch the movie and the movie’s box office success. The authors then propose an optimization procedure for cutting scenes from trailers to produce clips and test it in an online experiment and in a field experiment. The results provide evidence that the production of short clips using the proposed methodology can be an effective tool to market movies and other online content. [ABSTRACT FROM AUTHOR]

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization. [ABSTRACT FROM AUTHOR]

As the content industry develops, the demand for movie content is increasing. Accordingly, the content industry is actively developing super-personalized recommendation systems that match consumers' tastes. In this paper, we study automatic generation of movie tags to improve the movie recommendation system. We extracted background sounds from movie trailer videos, analyzed the sounds using STFT (Short-Time Fourier transform) and major audio attribute features, and created a genre prediction model. The experimental results show that the pre-collected dataset and the data extracted via the model are similar when compared. In this research, we suggest the methodology of an automatic genre prediction system for movie information from trailer videos. This will help to reduce the time and effort for metadata generation for a recommendation system. [ABSTRACT FROM AUTHOR]

Nowadays, merchants' marketing strategies have broken time and distance barriers, allowing consumers to interact with advertisements, and merchants can gather a large number of consumers' feedback at the same time. PRCB is proposed and used because it can engage and create consumers' interest prior to the release. Different from EWOM, PRCB is usually launched before product release, and such activities can be divided into three types: communication, search, and participation in experience activities. PRCB can accurately predict the development trend of products due to its dynamic nature, which was proven by introducing data on movie box office and movie trailer clicks. In addition, the VSM platform (HSX) is also introduced to show consumers' expectation and interest in new items by analyzing the evolving trend of the stock market. Finally, this paper discusses the universality of PRCB in different consumer groups and the research direction to further improve its prediction accuracy. [ABSTRACT FROM AUTHOR]

People consume and enjoy similar media entertainment as their friends and close others do. Yet the underlying psychological processes driving selection and consumption of entertainment considered "mainstream" within a group are still unclear. Given that individuals' behaviors and attitudes are influenced by the perceived prevalence of others' behaviors (descriptive norms) and perceptions of what others approve (injunctive norms), we examined the role of descriptive and injunctive norms in media selection and enjoyment. In an online experiment, we tested whether norm messages affected perceptions of group norms, and whether these perceptions influenced the enjoyment of a movie trailer and intention to watch the full film. We also tested the moderating roles of group identity and proximity on perceived norms and subsequent effects. Results showed that norm messages predicted perceived descriptive norms, which in turn predicted enjoyment of the trailer and intention to watch the film. Norm messages also predicted perceived injunctive norms, and the effect of injunctive norms on outcome variables was strengthened by group proximity and identity. The discussion highlights ways that social norms can inform understandings of socially-influenced media enjoyment and selection in future work and unique opportunities to study normative influence in a media setting. [ABSTRACT FROM AUTHOR]

Films have been held for a long-term tradition as a meaning-making practice in visual and audio play, in the hybridization of language, image and sound, as well as in interactive symphonization with the audience/viewers. Through the emerging theoretical lens of translanguaging, this article analyzes the translingual practices, performance, instances in a Chinese film entitled Love After Love (adapted from Eileen Chang's short story and directed by the Hong Kong Director Anne Hui), in which a Portuguese sonnet lyrical poem (Rimas) is delicately crafted in the film and projected in the trailer. Through this analysis, we aim to examine how translanguaging aesthetics transcend language boundaries, transforming from the seeming untranslatability to communicative meaning-making practice. The film presents a situated and embodied poem recital scene that encompasses untranslatable moments of imagination, thus transcending the Mandarin-English-Portuguese divide. The encounter and intertwining of heterogeneous languages and registers create a transformative space replete with tensions between reality and imagination, between lucidity and ambiguity, between resistance and compliance, interrogating the underlying discourses beyond languages and rendering the untranslatability meaningful. This translanguaging-informed film review thus offers an insightful autopsy of the literary aesthetics of the novel by Eileen Chang. [ABSTRACT FROM AUTHOR]