: Machine learning models suggest that poster information, specifically facial features and cast arrangement, can predict ratings with over 71% accuracy. 3. Sociological Reception and Cultural Proximity
This paper examines the evolution of Japanese television dramas (J-dramas) from the "trendy drama" era of the late 1980s to the current global streaming landscape. It analyzes how audience reception—historically centered on domestic ratings—has shifted toward online reviews and digital fan communities. By integrating structural industry data with sociological theories of "cultural proximity" and "Asian modernity," this study illustrates how digital platforms have transformed the consumption and critical evaluation of Japanese popular entertainment. 1. Introduction: From Traditional Theatre to Trendy Dramas : Machine learning models suggest that poster information,
: Actors such as Takuya Kimura (who maintains a 100% ratio in highly rated dramas) and screenwriters like Yasushi Fukuda are significant indicators of commercial success. Introduction: From Traditional Theatre to Trendy Dramas :
The foundation of Japanese drama lies in classical traditions like , Kabuki , and Bunraku , which emphasize stylized storytelling and emotional resonance. Modern television dramas, however, evolved significantly during the "Bubble Era" (1986–1991) with the birth of trendy dramas —urban, consumer-oriented love stories that mirrored the glamorous lifestyles of the time. Today, these series continue to leverage a "trendy" formula, often focusing on workplace relationships and social issues like bullying or domestic violence to foster audience empathy. 2. The Mechanics of Success: Ratings and Predictors specifically facial features and cast arrangement