Video media industries

The commercial features and distribution models of the movie, traditional television, streaming video and online video industries each exert an influence on the type of content produced, how it's crafted and how audiences engage with it. Despite the growth of other industries such as video games and social media, video media industries remain a cultural touchstone, providing (among other things) the main source of internet memes: “Far from rendering typical forms of pop culture vestigial, internet culture is built on a foundation of SpongeBob, Leonardo DiCaprio expressions, and obscure gaming references.”[1]

Digital audiovisual media services (AVMS), which include online video, digital music and digital gaming, rose to over $5.9 billion in revenue in 2021. The center of the network media economy, however, is shifting from advertising-supported media towards subscriber fees ("pay-per media"). This shift towards the pay-per model has made the television business more resilient to economic shocks compared to traditional advertising revenue. International corporations such as Amazon, Apple and Netflix are significant players in the Canadian landscape, generating an estimated $15.4 billion in revenue in 2021. However, the five biggest domestic companies (Bell, Telus, Rogers, Shaw/Corus and Quebecor) still account for just over two-thirds of all revenue across the network media economy.[2]

Film and broadcast television

For much of the 20th century, cinema and television were the primary forms of video, characterized by a highly centralized and professionalized industry model. In this era, the tools for video creation were largely limited to professionals, and distribution was rigidly controlled by corporate media gatekeepers. Content was typically licensed or commissioned by distributors, which implied a high financial investment per project. The primary goal was to reach a "mass media" audience, a norm that significantly shaped the social and cultural understanding of media. This commercial model requires content with high production values and a meticulous approach to visual storytelling to justify the significant investment and appeal to a broad audience,[3] and leads to decisions based primarily on avoiding risk: as Walt Hickey says in You Are What You Watch, “the top priority of most producers is not to make a lot of money, but rather not to lose a lot of money. Nobody ever got fired for making a modest bet on a beloved franchise, but many people have gotten fired for making a modest bet on an unknown script with big potential. The incentive is risk aversion, not profit seeking.”[4] Or, as podcast host Chris Winterbauer put it, “All it takes is one bad comp in Hollywood for a project to go the way of the dodo.”[5]

The Canadian television industry is unique internationally due to high levels of integration: major commercial broadcast TV and pay/specialty TV services are owned by large communication conglomerates (e.g., Bell, Rogers, Shaw/Corus and Quebecor). At the same time, the commercial TV business model in Canada has long relied on domestic entities, like Bell, buying exclusive, long-term rights to marquee US programming (e.g., HBO, Starz, Showtime) for distribution in Canada. This brokering model is increasingly jeopardized as international content providers go direct-to-consumer.[6]

Total investment in film and TV production in Canada reached $9.1 billion in 2021. This investment growth has been driven by foreign sources (e.g., traditional Hollywood studios and new streaming services like Netflix and Amazon). This trend results in a high volume of "foreign location service productions," which predominantly use the "commission-and-keep-it-all" model (where the financier retains sole rights to ownership). While this foreign investment creates a lasting legacy of local capacity creation (skilled workers, facilities), it often means that Canadian investors and producers forgo control over distribution, rights, and profits.[7]

Streaming video

Streaming video services (e.g., Netflix, Hulu, Disney+) distribute series, shows and movies based on licensed content, similar to the legacy model, but delivered over the internet. Their primary business models are subscriptions and advertising. Revenue for online video subscription and download services grew to $3.5 billion in 2021. Netflix is the largest online video service in Canada, holding 7.5 million subscribers (just over half of all Canadian households) and generating $1.34 billion in revenue in 2021. The advent of online video services has expanded the overall television market, indicating that the relationship is one of growth rather than pure cannibalization of existing revenue,[8] but over the last five years the main revenue source of streaming platforms has shifted from TV-length to feature films.[9]

While content on these platforms generally maintains the high production standards and narrative sophistication of traditional media, the distribution model influences how content gains popularity and is consumed.[10] The immediate availability of content on streaming platforms facilitates high rewatchability and can fuel virality through social media. For instance, the animated film "KPop Demon Hunters" became a phenomenon partly due to its immediate availability on streaming, which encouraged rewatchability and spurred fans to re-enact choreography on TikTok and share clips on platforms like YouTube.[11] This shows how streaming enables content to leverage networked effects and sustained engagement, particularly for content that lends itself to social sharing and repeated viewing. Distribution deals with studios, which shift risk and control to the streamer and often forgo traditional profit participation, can lead to content being produced with an eye towards streaming success metrics (e.g., viewership hours, completion rates) rather than solely theatrical box office performance.[12] At the same time, because each platform is an individual expense, streamers are constantly looking for ways to reduce “churn” (when consumers let their subscriptions lapse).[13]

Unlike theatrical film and broadcast TV, streaming video platforms typically make heavy use of algorithms to curate, recommend and even commission content. Netflix, for example, uses an interface that features both horizontal and vertically scrolling bars, populated algorithmically – the categories, the individual titles and even the specific thumbnail art are all selected based on what Netflix knows about the viewer. While the two-directional scroll provides a sense of abundance, the categories and titles are also sorted so the ones that the algorithm considers the best match are most prominently displayed.[14] This process uses at least six different ranking algorithms that consider things like a title's overall popularity, recent increases or decreases in its popularity, and its similarity to other videos in the same row and that the viewer has watched before. The thumbnails that represent each item are also selected algorithmically. Netflix reports that thumbnails draw 80 percent of a viewer's attention when browsing, and the brief window Netflix has to lead the viewer to a decision means these images must be carefully chosen to appeal to each viewer.[15]

The data collected by streaming video services isn’t only used to match users with items; it’s also used to make decisions acquiring and commissioning new content. This allows Netflix, for example, to hedge its bets by running a hypothetical new show or film through the recommendation system and also to pursue a "conglomerated niche" strategy,[16] using association algorithms to identify gaps in the market such as underserved audiences or unexpectedly popular microgenres.[17] 

Online video

The rise of online video sources, such as YouTube and TikTok, has decentralized traditional gatekeepers and redefined content creation and consumption. These platforms distribute video without creating or commissioning it. Users – a mix of professional, amateur and in-between – post content without any licensing agreement other than the platform’s terms of service. This shifts the risk almost entirely to the creator, in exchange for more creative agency and access to the platform’s audience. This model supports hobbyist and non-commercial video creation, leading to a vast quantity of content reflecting highly specific interests and sensibilities. While a few hosted videos achieve viral mass appeal, they are the exception; the strength of hosted video lies in its fragmentation and specialization. Content discovery is often algorithmically driven , through features such as YouTube’s “Up Next” bar and TikTok’s “For You” page, though it also blends with user input through "following" accounts or active searching.[18]

As a result of these technical and commercial features, online video typically has:

• Niche and personalized content: Online video excels at providing content tuned to personal interests, passions and sensibilities often unavailable in other video industries due to their need for broader audiences. Viewers use these platforms to pursue "personal favorite content" or "specific content," such as detailed gardening insights, comedy or engineering tutorials. Creators can specialize without needing to appeal to a mass audience.[19]
• Short-form and vertical formats: The immense popularity of TikTok, with its short-form, often vertical videos designed for infinite scrolling and quick consumption, has spurred other services (e.g., Instagram Reels, YouTube Shorts) to introduce similar features. This influences creators to produce content optimized for mobile, bite-sized engagement. The mobile accessibility of hosted video on phones enables its use in "in-between" moments throughout the day, providing quick entertainment when viewers "don't want to think deeply." This influences content design to be easily consumable in short bursts and across various, often casual, settings.[20]
• Emphasis on social interaction and sharing: Hosted video fosters "connection through sharing." Videos are often produced with the intention of being shared with friends and family via private messages, where friends act as "human algorithms" for relevant content. This distinct use case encourages creators to make shareable, relatable or conversation-starting content.[21]
• Viewer agency: Users are often "deliberate" in their engagement, actively curating their feeds and employing strategies to receive desired content, even amidst algorithmic suggestions. This means creators must produce content that resonates strongly enough for viewers to actively seek it out or engage with it despite the vast array of options. While motion is still present, the sheer volume and less consistently curated nature of user-generated content, especially in "Exploring" features (like TikTok's "For You" page), can lead to more dispersed and idiosyncratic gaze patterns compared to highly directed cinematic experiences. This allows narrative comprehension and individual searches for meaning to guide attention more freely, as the "tyranny of film" is weaker without the same level of exogenous control from motion.[22]

What viewers and creators refer to as "the algorithm" on platforms such as YouTube or TikTok is actually many different systems: association and classification algorithms are used to analyze user preferences, tag videos and recommend videos to users on that basis. User interactions are then evaluated based mostly on whether the user 'liked' the video, whether or not they commented on the video, how long each session lasted and how soon the user returned to the app after leaving. Those evaluations are used to further train the recommendation model for that user. The app’s interface is designed to encourage interaction by limiting what is visible on screen to the video and the interaction icons (like, comment and share). Showing a single video at a time also lets the platform more accurately measure how much of it you watched. 

Content creators' experiences are also shaped by platforms' use of algorithms, feeling pressure to make themselves more visible: "This logic shapes the topics discussed in videos, genres engaged with, video lengths, titles utilized, video thumbnail design, and organization of speech." However, if content is oriented too much towards the algorithm, it runs the risk of being "clickbait" and facing backlash from viewers.[23] Creators must therefore walk a fine line between catering to (what they perceive to be) the algorithm's preferences without being seen as trying too hard to do so – a line much easier to walk if what they produce is already favoured by the algorithm.

Creators are also pressured to produce and publish content more often to retain their algorithmic ranking. As one YouTube contributor noted, "the algorithm forces you to constantly produce content. So you can't be like, I'm going to do a short film and take a break for like a month and a half because short films take time. You can't do that. You are going to lose hundreds of thousands of followers, and you are not going to make money." The same research found that YouTube creators favoured design changes that would reduce the “rich-get-richer” effect and promote serendipity: specifically, letting viewers see what their friends are watching, showing viewers the content they wouldn’t otherwise click, promoting more human-curated recommendations and promoting new or less popular creators.[24]

[1] Hickey, W. (2023). You Are What You Watch: How Movies and TV Affect Everything. Hachette UK.

[2] Winseck, D. (2022) Growth and Upheaval in the Network Media Economy, 1984-2021. https://doi.org/10.22215/gmicp/2021.1. Global Media and Internet Concentration Project, Carleton University.

[3] Lotz, A. D., & Lunardi, G. (2025). Understanding hosted video and its uses: Conceptualizing new fields of video experience. New Media & Society, 14614448251338490.

[4] Hickey, W. (2023). You Are What You Watch: How Movies and TV Affect Everything. Hachette UK.

[5] Winterbauer, C. (2025) What Went Wrong: Predator. Sad Boom Media.

[6] Winseck, D. (2022) Growth and Upheaval in the Network Media Economy, 1984-2021.

[7] Winseck, D. (2022) Growth and Upheaval in the Network Media Economy, 1984-2021.

[8] Winseck, D. (2022) Growth and Upheaval in the Network Media Economy, 1984-2021.

[9] Rojas, A. (2025) How Movies Increasingly Drive Streaming Revenue. The Hollywood Reporter.

[10] Lotz, A. D., & Lunardi, G. (2025). Understanding hosted video and its uses: Conceptualizing new fields of video experience. New Media & Society, 14614448251338490.

[11] Fuster, J. (2025) The ‘KPop Demon Hunters’ Craze Couldn’t Have Happened in Movie Theaters. The Wrap.

[12] Belloni, M. (2025) The Tragedy of ‘KPop Demon Hunters.’ Puck.

[13] Rojas, A. (2025) How Movies Increasingly Drive Streaming Revenue. The Hollywood Reporter.

[14] Alvino, C., & Basilico J. (2015) Learning a Personalized Homepage. The Netflix Tech Blog. Retrieved from https://netflixtechblog.com/learning-a-personalized-homepage-aa8ec670359a

[15] Nelson, N. (2015) The Power of a Picture. Netflix blog. Retrieved from https://about.netflix.com/en/news/the-power-of-a-picture

[16] Higson, A. (2021). Netflix, the Curation of Taste, and the Business of Diversification. Studia Humanistyczne AGH, 20(4), 7-25.

[17] Carr. D. (2013) Giving Viewers What They Want. The New York Times. Retrieved from https://www.nytimes.com/2013/02/25/business/media/for-house-of-cards-using-big-data-to-guarantee-its-popularity.htm

[18] Lotz, A. D., & Lunardi, G. (2025). Understanding hosted video and its uses: Conceptualizing new fields of video experience. New Media & Society, 14614448251338490.

[19] Lotz, A. D., & Lunardi, G. (2025). Understanding hosted video and its uses: Conceptualizing new fields of video experience. New Media & Society, 14614448251338490.

[20] Lotz, A. D., & Lunardi, G. (2025). Understanding hosted video and its uses: Conceptualizing new fields of video experience. New Media & Society, 14614448251338490.

[21] Lotz, A. D., & Lunardi, G. (2025). Understanding hosted video and its uses: Conceptualizing new fields of video experience. New Media & Society, 14614448251338490.

[22] Hutson, J. P., Chandran, P., Magliano, J. P., Smith, T. J., & Loschky, L. C. (2022). Narrative comprehension guides eye movements in the absence of motion. Cognitive Science, 46(5), e13131.

[23] Bishop, S. (2020). Algorithmic experts: Selling algorithmic lore on YouTube. Social Media+ Society, 6(1), 2056305119897323.

[24] Pedersen, E. (2019). “My Videos are at the mercy of the YouYube algorithm”: how content creators craft algorithmic personas and perceive the algorithm that dictates their work. (Master's Thesis). Berkeley, CA: University of California at Berkeley.