The Unraveling of Social Media: A Glimpse into the Future Landscape
Meta recently asserted their bold move towards reinventing Facebook's newsfeed to rely significantly more on an algorithmic, recommendation-based model of content dissemination. This significant shift underlines Meta's dedication to the application of cutting-edge strategies in content distribution. Though other top-tier platforms, including Meta's Instagram, have been slowly steering towards this approach, Facebook's definitive step heralds a new phase in social media's evolution. As the most expansive social network globally, Facebook's strategic shift carries far-reaching ramifications for how users will interact with and consume content on the platform.
Notwithstanding, there has been resistance to this transition. Prominent social media figure Kylie Jenner voiced her dissatisfaction with Instagram prioritizing suggested videos over friends' photos. With her commanding following of over 360 million on Instagram, Jenner's sentiment wields substantial influence. Her previous criticism of a change to a social network, Snap, led to a 7% dip in their stock price. Therefore, it's not a surprise that Instagram's CEO, Adam Mosseri, addressed these recent alterations and future plans in a video. Mosseri conceded that the world is in a state of flux, and Instagram must be prepared to adapt.
Yet, these changes towards algorithm-driven feeds over friend-driven feeds are rational. Platforms like TikTok and YouTube, which are immensely popular and continuously growing, place less emphasis on friends and social connections and more on meticulously personalized, enchanting algorithmic experiences that deliver the right content to the right person at the perfect moment. This is known as recommendation media, the new norm for content distribution online.
Social media, in essence, refers to content (text, images, videos, audio, etc.) disseminated primarily via networks of interconnected individuals. This distribution model assures creators a certain level of reach based on their network of friends or followers, providing them considerable power as they have built-in audiences for their content. Consequently, social media becomes a competition based on popularity, not content quality, favoring creators with larger followings for distribution and influence.
These dynamics allow social media platforms to expand swiftly. If a platform can establish a social network, it inherently possesses a distribution system for serving engaging, highly relevant content to vast audiences. However, this approach has also had adverse effects for platform companies, the internet, and society at large. The ease with which content can be shared often leads to the dissemination of problematic content, creating polarized discussions and conflicts.
This is where recommendation media steps in. Instead of primarily distributing content to networks of connected people, recommendation media relies on opaque, platform-specific algorithms that seek maximum consumer attention and engagement. The platform decides what consumers won't see, such as problematic or divisive content. It's ultimately the platform's call on what content gets recommended, not the person producing the content's social network. This change puts less emphasis on popularity and more on the quality of the content.
With recommendation media, the best content for each consumer is prioritized, resulting in a superior consumption experience. This shift explains why a figure like Kylie Jenner might oppose this transition; her legion of followers carry less weight in an algorithm-dominated landscape. The platform also gains the power to decide what becomes popular and when.
In recommendation media, with no guaranteed content distribution through friend networks, creators are compelled to find engagement elsewhere if it's lacking on their current platform. This shift can spur massive growth on the original platform. For instance, whenever TikTok content is shared on Twitter, users who wish to consume that content click through to TikTok, thereby driving engagement and potentially attracting new users.
With Facebook's formal move to recommendation media, it appears we are on the cusp of a new internet era, and the future remains an exciting mystery. As has been the trend with previous internet generations, platforms will always strive for greater efficiency as technology continues to evolve.
What's your take on this? Is the era of social media drawing to a close? Or could this pave the way for a challenger to revitalize the traditional social media model?
References
Article: "The Rise of Recommendation Media: What it Means for Social Platforms and Content Creators" - This in-depth article delves into the concept of recommendation media and its impact on social platforms and content creators. It analyzes the benefits and drawbacks of algorithm-driven content distribution and discusses how it is reshaping the way we consume and interact with online content.
Podcast: "Navigating the Future of Social Media: From Social Graphs to Recommendation Algorithms" - In this podcast episode, industry experts discuss the implications of the shift from social graphs to recommendation algorithms in social media platforms. They explore how this transformation is affecting user behavior, content creation, and the overall dynamics of social media ecosystems.
