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The goal of the study is to underline “Cinematic Architecture” as another source of architectural thinking and research. This study is also a response to the shortage in empirical research on architecture in the cinema. Moreover, the study introduces the architectural components that qualify the cinematic spaces to be influential cinematic experience. This is in addition to investigating the impact of these components on the viewers' cognitive and emotional experience of films.

In the reported study, an empirical experiment examined scenes from three different movies as experienced by a selected group of audience of movies fans (architects and laypersons). The audience was asked to report feelings the audience had about each scene using a questionnaire that was designed for this purpose, and the audience was asked to write down the aspects that affected the audience's emotions. The experiment evaluated selected emotional states and could specify the architectural features and/or objects that significantly contributed in inducing these emotions.

This study's findings concluded that emotions, which exist in the positive margin of the emotions “circumplex model,” were influenced by architectural components that were different from those that influenced emotions which lie in the negative margin of the model.

As for filmmakers, the study contributes in developing filmmakers' knowledge about the role of architecture in scenic creation and thus how that knowledge enhances filmmakers' film narrative and the narrative's spatial imagery. As for academia, this study contributes in developing the knowledge about film cognition as related to architectural semiotics. In the context of behavioral approach to architectural design, a behavior setting which is the basic element in environmental design can be dramatized by applying a cinematic narrative to a human activity system within a milieu of architectural design elements.

This study is important for architects, as the study provides architects with an alternative tool for fictional experience and for testing architectural ideas through cinematic architecture. This study also helps in developing new venues for the practice of architecture into the world of fiction. This study also contributes in developing the trend that architectural design thinking can learn from cinematic thinking and practice.

This study introduces an empirical approach to evaluate architectural entities as part of cinematic experience. This study also comes as a response to the shortage in empirical research on architecture in the cinema.

This study aimed to identify subgroups of esports players based on their gaming behavior patterns across game genres and compare self-efficacy, social efficacy, loneliness and three dimensions of quality of life between these subgroups.

324 participants were recruited from prolific academic to complete an online survey. We employed latent profile analysis (LPA) to identify subgroups of esports players based on their behavioral patterns across genres. Additionally, a one-way multivariate analysis of covariance (MANCOVA) was conducted to test the association between cluster memberships and development and well-being outcomes, controlling for age and gender as covariates.

LPA analysis identified five clusters (two single-genre gamer groups, two multigenre gamer groups and one all-genre gamer group). Univariate analyses indicated the significant effect of the clusters on social efficacy, psychological health and social health. Pairwise comparisons highlighted the salience of the physical enactment-plus-sport simulation genre group in these outcomes.

This study contributes to the understanding of the development and well-being benefits experienced by various esports consumers, as well as the role of specific gameplay in facilitating targeted outcomes among these consumer groups.

This paper aims to explore how music festival organisers negotiate diversity and inclusion in marketing and promotion practices through symbolic and social boundaries.

Based on semi-structured interviews with 18 festival organisers in Rotterdam and participant observation with six festival photographers I show that symbolic and social boundaries are employed in three areas: (1) boundaries in festival format (i.e. [partially] free or ticketed), (2) boundaries in distribution partners and technologies and (3) boundaries in promotional content.

Symbolic and social boundaries are intentionally used by festival organisers to build and delineate festival audiences. Implications are drawn on current understandings of the accessibility of music festival spaces, arguing that festival research should move beyond within-space dynamics to grasp the negotiation of diversity and inclusion at festivals more fully.

While music festivals are often marketed as celebratory spaces that are “welcoming to everyone”, few studies have investigated diversity and inclusion nor marketing and promotion practices at music festivals. This study shows how festival audiences are shaped through marketing and promotion practices.

Anecdotal evidence suggests that casting actors with similar facial features in a movie can pose challenges in foreign markets, hindering the audience's ability to recognize and remember characters. Extending developments in the literature on the cross-race effect, we hypothesize that facial similarity – the extent to which the actors starring in a movie share similar facial features – will reduce the country-level box-office performance of US movies in East and South-East Asia (ESEA) countries.

We assembled data from various secondary data sources on US non-animation movies (2012–2021) and their releases in ESEA countries. Combining the data resulted in a cross-section of 2,616 movie-country observations.

Actors' facial similarity in a US movie's cast reduces its box-office performance in ESEA countries. This effect is weakened as immigration in the country, internet penetration in the country and star power increase and strengthened as cast size increases.

This first study on the effects of cast's facial similarity on box-office performance represents a novel extension to the growing literature on the antecedents of movies' box-office performance by being at the intersection of the two literature streams on (1) the box-office effects of cast characteristics and (2) the antecedents, in general, of box-office performance in the ESEA region.

The global prominence of languages and Saudi Arabia’s Vision 2030, which supports the necessity of German proficiency for the nation’s socioeconomic evolution, necessitate a deeper understanding of German teaching in Saudi international schools. This study delves into the influence of various teaching strategies on students' German writing skills. The research particularly focuses on traditional and innovative methods and considers the factors that drive these teaching approaches.

Data were collected from 304 students in Riyadh, Saudi Arabia, through a questionnaire. The relationships between teaching strategies and students' German writing abilities were analyzed using regression techniques.

The results indicate that both traditional and innovative teaching strategies positively influence students' writing skills. The regression analysis shows that the independent variables (traditional teaching strategies, innovative teaching strategies and factors influencing teaching strategies) collectively account for 68.9% of the variation in students' German writing skills. Even though a variety of techniques influence students' academic performance, the study’s findings indicate that several strategies – such as self-evaluation, pair work, oral feedback, grammar instruction and translation – have a major impact on students' German writing abilities.

This research brings unique insights into the German teaching realm of Saudi international schools, emphasizing the harmony between Vision 2030 goals and effective teaching methodologies. It elucidates the considerable influence of both traditional and innovative strategies on student writing outcomes. For educators in Saudi Arabia’s international educational environment, the study’s findings underline the importance of adopting student-centric approaches in the writing process, ensuring students evolve as proficient writers. Additionally, the research underscores the significant role of variables affecting teaching strategies, spotlighting their pivotal role in shaping student outcomes.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

This paper aims to examine how museums reach Generation Z virtual tourists using TikTok videos to elucidate the relationship between the video elements and types of engagement by classifying the characteristics of popular themes in the museums’ short videos.

The format, type and content of TikTok videos published by the seven international museums with the most popular TikTok accounts were analyzed. Thematic analysis included 313 short TikTok videos randomly chosen from those published by the museums between 2020 and 2022. Using descriptive analysis, museum-related TikTok usage and user engagement are presented; regression analysis revealed the most significant themes for audience engagement.

Museum promotions commonly use several strategies, including incorporating text-based information, captions, hashtags and background music into the video formats. Oral speech/documentary-style videos and combined video genres are less common. The most frequently presented video topics included history, infotainment, informative content and promotional elements. The results identify specific formats (titles and subtitles), types (demonstrations, news/events and TikTok dances/movements) and promotional themes that result in audiences’ virtual engagement in the form of “likes” and “comments” and increase the museums’ TikTok channel followers.

The results demonstrate that short videos on social media platforms encompass various strategies involving different formats, types and themes. Museums can use these strategies to engage virtual tourists. This study also provides valuable suggestions for museums and galleries seeking to leverage short videos as effective marketing mechanisms.

The effectiveness of rhetorical structure is essential to communicate key messages in research articles (RAs). The interdisciplinary nature of library and information science (LIS) has led to unclear patterns and practice of using rhetorical structures. Understanding how RAs are constructed in LIS to facilitate effective scholarly communication is important. Numerous studies investigated the rhetorical structure of RAs in a range of disciplines, but LIS articles have not been well studied.

In this study, the authors encoded rhetorical structures to 2,216 articles in the Journal of the Association for Information Science and Technology covering a period from 2001 to 2018 with the approaches of co-word analysis and visualization. The results show that the predominant rhetorical structures used by LIS researchers follow the sequence of Introduction-Literature Review-Methodology-Result-Discussion-Conclusion (ILMRDC).

The authors' temporal examination reveals the shifts of evolutionary pattern of rhetorical structure in 2008 and 2014. More importantly, the authors' study demonstrates that rhetorical structures have varied greatly across research areas in LIS community. For example, scholarly communication and scientometrics studies tend to exclude literature review in articles.

The present paper offers a first systematic examination of how rhetorical structures are used in a representative sample of a LIS journal, especially from a temporal perspective.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.