Draft:MovieTok

• Comment: There is potentially an article here but the tone is inappropriate for a Wikipedia article, and I would also cut down the content substantially to just be the core idea of the subculture. qcne (talk) 16:33, 17 November 2024 (UTC)

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MovieTok is a subcommunity of the app TikTok that is focused on movies and movie criticism. Users create content such as reviews, discussions, and memes about movies they have watched as well as share behind-the-scenes gossip and industry rumours. This trend closely resembles the BookTok subcommunity, both having similar impacts on culture perception and economic-marketing processes of the respective industries.

Background

It is widely recognised that TikTok significantly shaped — and continues to shape — culture and its perception among Gen Z, and, by extension subsequent generations. Numerous examples highlight how musical artists have gained fame through the platform or how vintage records, unacknowledged by the younger generations, can experience a renaissance thanks to the platform. Indeed, TiKTok’s influence in driving trends is undeniable. For instance, in fashion and cosmetics, TikTok has modelled consumer preferences and behaviours: viral products include Amazon’s butt-lifting leggings, Girlfriend Collective bras, L’Oréal Telescopic Mascara, and Revolution Pro Face Primer — all of which saw surges in sales after gaining traction on TikTok. Indeed, TikTok has transformed consumer culture and purchasing behaviour: a 2021 study by Adweek and Morning Consult found that 49% of TikTok users bought products and services after seeing them promoted by the platform..

Among TikTok’s many cultural impacts, the movie industry is no exception: From FilmTok figures like critics David Ma and Hunter Clark to TikTok’s official partnership with the Cannes Film Festival, the ties between this new media and the movie industry are numerous. The platform harnesses fandoms, subcultures, and niche genres, propelling them into mainstream consciousness. Many have also linked this to the drive in box-office sales. Content creators on the platform, whether discussing new releases or older films, are directing audiences to cinemas and streaming services alike. This content creates trends which ultimately substantially help a movie to become famous; notable examples include the #gentleminions trend, where Gen Z fans attended screenings dressed in suits mimicking Gru’s gestures, and the “Barbie trend”, where fans flocked to theatres dressed in pink for screenings of the Barbie movie .

Given the magnitude of said phenomenon, a closer look at the following dilemma is necessarily: what role has MovieTok played in the mainstream film culture and consumption habits? This question is key as, by being broad, it can tackle a wide array of phenomena within FilmTok, spanning from box-office success and the “theatre renaissance” to film-determined fashion trends as well as music/soundtracks production. While it is acknowledged that Movietok and other social media trends linked to it have contributed to a resurgence of interest in classic movie literature, this revival may not be entirely positive. This trend may, indeed, often involve exploitation, misinterpretation, oversimplification, and superficial engagement with these works, raising concerns about the depth of understanding within this new movie renaissance.

Emergence

Since the creation of social media in 2004, the relationship of information has changed, and was no longer a strictly one-way mode . New media (which TikTok finds itself a part of) is distinct from traditional media because of various factors such as visuals, function, music, and narratives.

Firstly, in order for such a short video to capture the attention of individuals, the visuals need to be much more beautiful and aesthetically pleasing than traditional media (which has a much longer timeframe to work with) . Thus, bright colours and quick movements/ transitions are more likely to be employed to create a high impact visual scene. Furthermore, beauty filters and various other filters (such as timewarp, hologram etc.) strengthen the visual component . Secondly, the function of the media has shifted too. Short form media, because of the time constraint, has the function of transmitting the most important information in under a minute in the most effective way. This phenomenon can be illustrated through the emergence of the “move commentator” . In these TikTok videos, a 90-120 minute movie (a piece of traditional TV media) is condensed into a minute long video where the commentator (which is normally an AI automated voice) outlines the ‘most important information’ . Additionally, musical features have changed. In traditional TV media, the music is most normally added after filming, with music dependent on the content, and so the removal of the added audio would likely not change the theme. On new social media platforms, creators often choose the audio first (i.e. before filming) and then choose to centre their content and their theme around the chosen audio . Lastly, the narratives in short form media need not be complex, compared to their older counterparts. There is no active need for complex plot lines or storytelling techniques such as foreshadowing .

Culture

MovieTok has circulated across the internet in general, having impacts on how movie content is consumed online. TikTok’s algorithm (more technically known as its recommender system) pushes forward videos based on users’ online behaviour and interactions, and as a result has influenced how recommendations are distributed and criticised by online users .

Information Cocoons

Information cocoons, formed by the algorithm of TikTok, means that social media users become entrenched in only their own preferences . Discussions of this media as a result become similar to each other and result in the same opinion being restated. Media discussion, while it has become a two-fold flow of information and communication, has become fragmented, yet hasn’t reached levels of fragmentation anticipated .

Distribution of TikTok Recommendations

According to the TikTok Help Center, the platform’s recommendation algorithm functions by analyzing numerous signals from a user’s behavior to determine the most relevant content for them. These signals include actions such as likes, comments, follows, and the duration of time spent watching specific videos. This data shapes the content displayed on the user’s “For You” page and the order in which it appears.

The algorithm is designed to create a personalized experience. Upon initial sign-up, TikTok may prompt users to select interest categories, which assist in tailoring the For You and LIVE feeds. If no categories are selected, a feed of popular, broadly appealing posts is provided, influenced by the user’s location and language settings, The system may also suggest well-known creators to follow. As users being engaging with content, their interactions serve as signals that guide the recommendation system in predicting preferred and less preferred content. This interaction data informs how content is ranked and presented to each user.

The For You feed delivers a continuous stream of content customized for individual preferences, helping users discover content and creators that resonate with them. Several factors influence what appears on this feed, including users’ interactions (likes, shares, comments), content details (sounds, view counts, hashtags) and user information (device settings, location, time zone). These factors are used to assess how relevant and engaging content might be for users.

Improvements to the Recommendation System and the Problem with Neighborhood Models

Recommendation systems are usually not perfect. Inspired by the 2006 Netflix Challenge, authors Dan Ehrlich and Johnny Ma published an article titled Letterboxd Collaborative Filter Recommendation System, analyzing the limits of recommendation systems . They argued that the filtering and recommendation systems presented at the challenge were not entirely satisfactory, especially when compared to real-life recommendations. They propose developing an enhanced algorithm designed to produce more accurate suggestions, specifically by achieving a lower Root Mean Square Error (RMSE).

The researchers source the data used to run their algorithms from the website Letterboxd which, unlike Netflix, provides numerous ratings from a wide array of users. The Letterboxd dataset is detailed: being diary-structured, Letterboxd displays a wide array of users and movies’ data as well as a ’taste profile’ of the user. The authors gather information automatically through web scraping by writing a program that extracts the needed data. From this, they develop a data frame where the rows represent the users data, the columns the films and values the ratings associated with both users and films. The data needed for the data-frame was taken directly from Letterboxd, respectively from users’ profile pages and the film list page. This led to three main data categories: user information, film information, and film-to-user information – that is, the rating a user u gives to movie i.

Once the data is gathered, the authors test the various approaches proposed at the Netflix Challenge using the Letterboxd data in order to find the most efficient recommendation system. Three naive models – pattern matching algorithms – are tested. The three models include (1) an aggregate model, which assesses the contribution of every movie to the average rating, (2) an ‘movie-focused’ model, which searches for the value of a single given movie to its average rating, and (3) an ‘individual-focused model, which calculates the predicted value with respect to the individual. The naive model yields the highest RMSE. Secondly, they test the baseline latent factor model – a recommendation system that identifies hidden patterns in user-item interactions. This model is based on mathematical formulas that generate a movie recommendation based on filters – or variables – such as ratings (rui), average rating (), movie bias (bi) and user bias (bi). After solving the equations, the predicted ratings can be calculated using the principal formula, which yields a RMSE of 1.5150, which is better than previous naive models. However, it is still considered relatively high. Thirdly, the neighbourhood model – a recommendation system that assumes similar users tend to have similar behaviours – is applied based on the Pearson's R test. The resulting RMSE value from this approach is 1.291371, which is the lowest among all the models we tested.

Despite being the best model of recommendation system, neighbourhood models are still likely to be mistaken, and, most importantly, they jeopardize the democratic aspect of social media platforms, as discussed in the further sections.

Reshaping of Movie Criticism

Democratization of the movie criticism

The rise of MovieTok has profoundly reshaped the landscape of film criticism, marking a shift toward a more accessible, user-centred model. The MovieTok community reflects a growing demand for intriguing, relatable film reviews that align with TikTok’s fast-paced, visually engaging format . MovieTok creators constitute a large audience, creating film commentary that is often described as less formal than traditional film criticism, offering a different approach that resonates with younger audiences prioritising a more conversational and visual approach.

This movement represents what some critics argue is a “death of film criticism” . MovieTok is critiqued for lacking a critical approach that has been the main axis of the field from its roots. Its focus on entertainment and relatability risks reducing complex films to simple trends, losing the depth and intellectual discourse that traditional critics have endorsed.This format encourages popularity over rigour, resulting in content that aligns more closely with popular opinion than critical analysis, a shift that might undermine the depth of cinematic appreciation .

Nonetheless, MovieTok creators have democratised film commentary, making it more accessible and appealing to a wider, more diverse audience. By selecting films that resonate with their followers and often collaborating with studios for promotional content, MovieTok creators have made film critique a part of mainstream entertainment. Yet, this popularity also raises ethical concerns. While many creators emphasise their independence, partnerships with studios can blur the line between genuine critique and paid promotion, sparking debate about the platform’s authenticity and impact on audience trust .

MovieTok represents both a transformation and a challenge for the field of film criticism. It is reshaping how audiences engage with cinema, making way for a dynamic, relatable model that thrives on social interaction. MovieTok undeniably underscores a new era in film discourse, one where influence is driven as much by audience engagement as by traditional critical insight .

Counter to the democratization

However, algorithms like those found on TikTok may undermine the democratic ethos of platforms like MovieTok and Letterboxd. Consequences of this include the amplification of select voices, which exposes users to the risk of taste homogenization .

Platforms like TikTok employ algorithms that play a role in determining which information is deemed most relevant, thereby choosing which voices are amplified and which are sidelined . Recommendation algorithms are not necessarily programmed to promote cultural diversity or pluralism but to suggest content based on their unique criteria. Sophisticated recommendation systems, like the neighborhood model, can reinforce existing preferences by presenting content closely aligned with users' established tastes . This creates echo chambers 2, where users are repeatedly exposed to similar types of films, leading to "algorithmic curation" that intensifies cultural standardization

Such practices may inadvertently narrow the scope of film discourse, privileging familiar and popular content over more experimental and unconventional works.

Adaptation of the Movie Industry

On a commercial scale, MovieTok has largely impacted the movie production industry. Since the end of the Covid-19 lockdown, a new sense of normalcy has returned to life as movie theatres have become fully operational again. Movie productions are back in full swing, and people are returning to theatres to watch the latest releases. However, despite this return to pre-pandemic life, the movie industry is experiencing a notable decline in audience attendance, with box office tickets selling at less than two-thirds as much as they did before lockdown measures in 2019. The movie industry’s decline can be attributed to the rise of online streaming services and the lasting effects of the pandemic, as well as inflation and supply chain issues. These factors play a role in the financial instability and lack of creativity in the industry as many production companies are choosing to stick to already popular franchises rather than branch out.

On the contrary, TikTok and other social media platforms experienced a boom in engagement since the beginning of lockdown measures in 2020. By 2023, TikTok recorded 1.9 Billion users worldwide, compared to just 653 Million in 2019. Particularly, TikTok is playing a key role in the post-pandemic shift in film marketing, as Gen Z and Millenials have become less reliant on official film reviews and trailers to be incentivized to see a film in theatres, but rather on peer suggestions and social media trends and MovieTok creators.

Through a user-friendly interface, interactive content, and the encouragement of user-generated content, TikTok captured the engagement of younger audiences. The movie industry has created personalized and exclusive content, releasing behind-the-scenes footage, following online trends and implementing features to make moviegoers feel more connected and interactive with the film industry.

Younger generations have become less susceptible to traditional movie marketing strategies, and are more reliant on social media to be exposed to upcoming films. In addition, TikTok allows users to consume movie reviews and summaries created by MovieTok. Moreover, TikTok’s “For You” algorithm tailors content to users’ interests using AI. This strategy leads to the addictive “infinite scroll” phenomenon which is emphasized by TikTok’s simple interface and full-screen experience. The endless stream of short videos found on TikTok capitalizes on shrinking human attention spans and the platform’s information cocoons feed users similar content on specific topics, such as MovieTok. While this explains TikTok’s dominance in the cultural sphere, it also shows how certain films are more popular than others. Content made regarding those films becomes popular and is then almost exclusively circulated to wider or specific audiences.

One recent example is that of the #GentleMinions trend where moviegoers dressed up in suits to go see the movie, Minions: The Rise of Gru. This resulted in this children’s movie being propelled into a global powerhouse and becoming the ninth-highest-grossing debut for an animated film in the United States. This phenomenon details how TikTok trends shape the scope of what audiences, specifically younger audiences, are attracted to and what they choose to go see in person.

Another important example of the Movie Industry capitalizing on MovieTok is that of the Barbie movie which came out in the summer of 2023. Barbie capitalized on the advantages of social media and MovieTok by creating shareable content that spanned multiple platforms. For instance, months before the film came out in theatres, the production released a “Barbie Selfie Generator” that allowed users to create personalized Barbie posters, encouraging user-generated content. The campaign also partnered with influencers to further amplify the movie's reach. Consequently, TikTok and Instagram were flooded with Barbie-themed posts and promotions for the movie. In addition, the “Barbenheimer” phenomenon which pitted Barbie against it’s release date twin Oppenheimer in a competition for biggest box office success. As a result, there was a boost in engagement with both movies as people felt personally involved in the success of one movie over the other and a variety of user-generated content such as memes took over social media. In the end, Barbie became the highest grossing film in 2023, earning over $1.4 billion (USD) worldwide.

Popular MovieTok Movies

These MovieTok Movies are ones that are discussed and referenced in depth on the platform. They include:

• Coraline (2009): This stop-motion animated film follows a young girl who discovers a dark alternate world, known for its eerie atmosphere and themes of self-discovery and bravery​.
• Fight Club (1999): This film explores the disillusionment of modern masculinity and consumerism, featuring an infamous twist and profound psychological depth that continues to spark debates on MovieTok​.
• American Psycho (2000):A psychological thriller that critiques 1980s excess and consumerism through the lens of Patrick Bateman, a businessman with a hidden violent side​.
• Scott Pilgrim vs. the World (2000):This visually unique film blends romance, action, and video game culture, following Scott Pilgrim as he battles his girlfriend's seven evil exes​.
• Barbie (2023): This satirical and feminist take on the iconic doll explores themes of identity and empowerment, resonating with a wide audience and generating extensive discussion on TikTok​.
• Oppenheimer (2023): Christopher Nolan’s historical drama delves into the life of J. Robert Oppenheimer and the creation of the atomic bomb, sparking debates on morality and scientific responsibility​.
• The Matrix (1999): A groundbreaking sci-fi film that questions the nature of reality, technology, and free will, frequently analysed for its philosophical implications​.
• Hereditary (2018):This horror film examines family trauma and grief, with an unsettling narrative that explores dark psychological and supernatural forces​.
• The Truman Show (1998): A film that satirises reality TV and privacy issues by following Truman, a man unknowingly living in a staged world, sparking discussions on media manipulation and autonomy​.
• The Lighthouse (2019): This psychological horror film, set in a remote lighthouse, explores madness and isolation through intense performances and surreal imagery​.
• Pulp Fiction (1994): Quentin Tarantino’s non-linear crime masterpiece is celebrated for its iconic dialogue, cultural impact, and themes of fate and redemption​.
• The Shining (1980): A psychological horror classic from Stanley Kubrick, this film’s portrayal of isolation, madness, and supernatural terror remains a frequent subject of deep analyses on TikTok​.