Content
1. Setting the Scene
From a simple toy to an expansive transmedia story world, Barbie has invited audiences into a universe of imagination and self-discovery since her debut 65 years ago. What began as a single plastic doll in a black-and-white striped swimsuit has transformed into a multifaceted narrative, brought to life through animated films, digital games, books, and even a blockbuster live-action movie.
This case study explores Barbie’s unique journey as one of the few brands that evolved from a toy into a movie franchise, rather than following the typical path from film to merchandise. Barbie as a transmedia storytelling phenomenon, examining how she has transitioned from a simple toy into a multifaceted brand that engages audiences across various platforms. By critically assessing Barbie’s interactive narrative experiences and their design features, this study will highlight how transmedia storytelling concepts such as interactivity, immersion, and agency have been effectively utilised by the brand. It will demonstrate that Barbie's enduring popularity is not only because of the nostalgia, but also from her ability to adapt and resonate with today’s audience, making them feel inspired and capable through its imaginative storytelling.
Instagram is a leading social media platform owned by Meta that leverages machine learning algorithms for content recommendation at its core. It has over a billion users sharing photos and videos, making it a prime application domain for AI-driven content moderation and recommendation. Content moderation on Instagram uses AI classifiers to detect and remove content violating guidelines, while content recommendation algorithms personalise what each user sees in their feed and the Explore page. These algorithms process vast data in real-time, determining which posts are amplified to wider audiences and which are suppressed. Instagram’s shift in 2016 from a purely chronological feed to an algorithmic feed exemplifies the reliance on machine learning to make the most of your time by showing what you supposedly care about most . In practice, this personalisation has a profound impact on user experience and culture: the platform has become a cultural phenomenon that shapes beauty standards and social values. A growing concern is that Instagram’s AI-powered recommendation system appears to promote immodest or sexually suggestive content amplifying content that show more skin and revealing attire more aggressively than modest content.
This report is based on a small scale experimental analysis conducted on Instagram. In one example, a creator uploaded two nearly identical video some where the individual wore modest clothing and another with immodest attire. The modest reel reached 3 million views, whereas the immodest one reached 4.5 million, indicating a 1.5x increase in reach. Another creator carried out a similar experiment, two videos were uploaded with the same script, hashtags, and settings. One included a suggestive pose, gaining 2.2 million views, while the more clearly framed and non-suggestive version reached only 558,000 views. These findings highlight growing concerns that Instagram’s AI-powered recommendation system disproportionately amplifies immodest or sexually suggestive content. This report examines that phenomenon in depth, drawing on academic research, industry studies, and the above experiments to critically analyse Instagram’s algorithm, its objectives, the data and patterns it relies on, the actions it takes, and the resulting ethical issues and regulatory implications.



