by | Dec 3, 2023

The Inequity in Streaming Platforms

Analyzing Spotify’s and YouTube’s Algorithms and Terms of Service

The digital age has revolutionized the music and video industries, with streaming platforms like Spotify and YouTube dominating the landscape. However, as these platforms continue to thrive, concerns have emerged regarding the unequal distribution of wealth within their ecosystems. This essay aims to explore how the algorithms and terms of service employed by Spotify and YouTube contribute to the challenges faced by emerging artists, making it difficult for the bottom of the content creation hierarchy to make a sustainable income, while simultaneously facilitating the enrichment of the already wealthy.

Entry Barriers and the Struggle for Visibility:

a. YouTube’s Criteria for Monetization:
One significant hurdle for content creators on YouTube is the requirement to achieve 4000 watch hours and 1000 subscribers before they can monetize their channels. This poses a substantial challenge for newcomers who must compete in an oversaturated market to garner attention. The result is a scenario where only a select few can break through and start earning revenue, perpetuating a system where the rich get richer, leaving many struggling at the bottom.

b. Spotify’s Algorithmic Challenges:
Spotify’s algorithmic approach to music recommendations also plays a role in limiting the visibility of lesser-known artists. The platform’s algorithms tend to favor established artists with high play counts and popularity, making it difficult for emerging talents to gain traction. As a result, the majority of plays are concentrated on a small fraction of well-known artists, hindering the discovery of new, diverse voices.

c. Amazon
The Amazon algo only supports you it you can prove you can sell. In other words you have to bring your own customers to Amazon.

Compensation Disparities:

a. Spotify’s Payment Structure:
While streaming platforms like Spotify have undoubtedly changed the way we consume music, the compensation structure remains a point of contention. Independent and emerging artists often struggle to earn a livable income due to the platform’s payout model, where artists are paid per stream. This system disproportionately benefits popular artists, as their extensive play counts result in more significant revenue streams, leaving little for those trying to establish themselves.

b. Spotify’s Black Box Problem:
Spotify’s opaque revenue-sharing model contributes to the challenge of income inequality. Withholding payment for the first 1000 streams on each song creates a “black box” of revenue that only gets distributed to artists once they accumulate a substantial number of streams. This system creates financial uncertainty for emerging artists who may have to wait for an extended period before seeing any returns on their work.

c. Amazon

Amazon’s algorithm places a significant emphasis on self-driven sales for authors. To garner visibility, aspiring writers must prove their book’s market appeal through prior sales. Amazon’s support is contingent on demonstrated success, making it crucial for authors to bring their own buyers to the platform. Without an established track record, the algorithm may not prioritize or promote a book. Consequently, authors find themselves relying on proactive strategies like Facebook campaigns and email lists to drive traffic to Amazon. In this competitive landscape, the algorithm’s insistence on proven sales underscores the importance of authors taking charge of their book’s promotional journey.

While Spotify and YouTube have undeniably transformed the music and video industries, and Amazon likewise the publisher market for books, their algorithms and terms of service contribute to an environment where the rich continue to prosper, while the bottom of the content creation hierarchy struggles to make ends meet. Revisiting these platforms’ entry barriers, visibility challenges, and compensation structures is essential to fostering a more equitable ecosystem for emerging artists and creators. As these digital giants shape the future of entertainment, addressing these issues becomes imperative for fostering a more inclusive and sustainable creative landscape.

In other words: The rich get richer and the poor get poorer.

The Dynamics of Trending

Who determines what is trending on these platforms?

In the digital era, platforms like Amazon, YouTube, and Spotify have become the gatekeepers of content consumption, influencing what is deemed trending and capturing the attention of a vast audience. This essay seeks to delve into the intricate web of factors that determine what becomes popular on these platforms, examining the roles played by artists, market forces, and algorithms. Despite the seemingly democratic nature of these platforms, we will explore how the influence of algorithms may perpetuate wealth disparities by favoring established entities, leaving emerging creators at a disadvantage.

The Role of Artists:
Artists undoubtedly play a pivotal role in shaping trends on digital platforms. Their creativity, innovation, and ability to resonate with audiences contribute to the organic development of trends. Successful artists with a significant following can leverage their fan base to propel their work to the forefront. However, the inherent challenge lies in breaking through the noise, as emerging talents often face barriers in reaching wider audiences due to established preferences and the influence of algorithms.

Market Forces:
Market dynamics exert a considerable influence on what trends on platforms like Amazon, YouTube, and Spotify. Consumer preferences, cultural shifts, and societal trends collectively shape the market, creating demand for specific types of content. Artists and creators who align with prevailing market trends are more likely to gain visibility and popularity. However, the market is a complex and dynamic entity, making it challenging for creators to predict and adapt to shifting trends effectively.

The Dominance of Algorithms:

Algorithms, powered by sophisticated machine learning, are integral to the operation of digital platforms. While they aim to enhance user experience by presenting personalized content recommendations, the influence of algorithms on trending content is a double-edged sword. The “rich get richer” phenomenon is evident as algorithms rely on historical sales and streaming data to recommend content. This creates a loop where already popular content receives more exposure, perpetuating its popularity while hindering the visibility of lesser-known creators.

a. Money Flow and Algorithmic Bias:
Algorithms are inherently profit-driven, designed to maximize engagement and revenue for the platform. This bias can lead to a concentration of attention on commercially successful artists and content, favoring genres and styles with proven market appeal. Consequently, emerging artists face an uphill battle to break into algorithms’ favored recommendations, creating a system that amplifies existing disparities in wealth and popularity.

b. Limitations of Predictive Power:
Despite their sophistication, algorithms are not clairvoyant. They lack the ability to predict the success of a piece of content based solely on its artistic merit. Instead, they rely on historical data, which can perpetuate existing biases and limit the diversity of content presented to users. This reliance on past success further entrenches established artists in the upper echelons of popularity, making it difficult for newcomers to gain a foothold.

The dynamics that determine what trends on platforms like Amazon, YouTube, and Spotify are complex, involving a delicate interplay between artists, market forces, and algorithms. While artists contribute creativity, and market forces shape cultural preferences, algorithms wield significant influence by reinforcing existing trends. The challenge lies in fostering an ecosystem that balances profitability with inclusivity, ensuring that emerging creators have a fair chance to be heard amid the noise of algorithmic preferences. As these platforms continue to shape the digital landscape, understanding and addressing these dynamics become imperative for fostering a more diverse and equitable content ecosystem.

The primary objective of algorithms is to enrich their owners, the shareholders. Ambitious individuals are wholly influenced by postmodern thinking, advocating for a profit-centric approach based on competitive conquer-and-divide tactics. Contrary to the debunked “Trickle Down” economic theory of the eighties, money doesn’t flow down but trickles up, concentrating wealth at the apex of society’s pyramid. Personal experiences, like observing social dynamics in Santa Monica’s nightlife, highlight how validation mechanisms from centuries ago persist. Amazon’s strategic booklists, such as “Customers who viewed items in your browsing history also viewed,” capitalize on pre-validation, mirroring the psychological dynamics of market and mass psychosis formation. The algorithms, inherently, ensure this amplification.

When Dave and I go out to enjoy a beer in the Nightlife of Santa Monica it is very evident that if he take me, Len and Angel with him, hordes of women swarm around him. This doesn’t happen when he is alone.

This is a mechanism from thousands of years ago. If a man walks around with a women, other women will assume she has validated him and found him OK. So in this case they do NOT  need to validate Dave. They simply skip that step and walk right up to him. He is together with me and thus pre validated.

Amazon has a booklist called “Customers who viewed items in your browsing history also viewed” and another one “Customers who bought from this series also bought” – just to mention a few headlines that will program you to buy books from this lists – because they are PRE validated by a lot of other readers.

Playlists on Amazon and YouTube works the same way. They program your brain to believe that because millions of flies eat cow shit you should too! It feels great to be part of one big family! Right?

Market formation is the same as Mass Psychosis formation. The algorithms make sure to boost

You have no idea how much great Indie music there is out there!

Many years ago I found this song by Mark Petruzzi, If Only. It’s a simple song there is so much emotion in it that I still listen to it. https://indiemusicpeople.com/songs.aspx?SongID=52028&ArtistID=81334

And I still look for Indie songs and I find a lot. Do the same! Support great music! Fuck Spotify and fuck YouTube. Be your own hero!

Trinity Sisters Dirty Business Stop Trafficking

If you ever heard about Jack Reacher you should meet his sister!

Just like Jack, Debra is merciless in her pursuit of truth and justice. Both Jack and Debra are loners, but Deb needs to find her lost family. And being in the way of a determined woman proves fatal for mafias, trafficking rings and a few Government officials.

This is the story about Debra trying to find her sisters, one of them lost in trafficking. And there is a lot of cleaning to do. An Albanian trafficking ring, the Serbian mafia and even Fuckingham Palace are in danger when Deb goes hunting.

What They Say:

“The best book ever! I was very happy to have the honour of doing the preface!”

Dave Snyper
Dont Fuck With Daddy

As a former soldier I am impressed by Debra’s story. I read the entire book in 3 hours just to start all over an read it again!

Glenn Miller

I was mesmerized and properly educated. Dirty Business is the most capturing book I have read.


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