About ten years ago, logging into Facebook, Twitter, or Instagram would mostly show posts from friends and family in the order they were posted. Today, these platforms present a mix of content, tailored by algorithms (算法) to match users’ interests, whether it’s plants, sports, cats, or politics.
Kyle Chayka, a writer for The New Yorker, discusses this topic in his book, Filterworld. He explains that algorithms analyze user data to predict and influence what they will likely engage with. This means that instead of a simple, chronological feed, users encounter a dynamic stream, constantly adapting to their preferences. Chayka examines how these algorithmic recommendations control what we consume, from music and movies to food and travel destinations. He argues that this machine-driven selection process has turned us into passive consumers, making our preferences and tastes more similar.
Chayka points out that algorithms make us passive by always showing us content that we’re unlikely to click away from but won’t find too unexpected or challenging. This constant stream of recommendations reduces our exposure to diverse or challenging content, subtly shaping our preferences and behaviors.
Moreover, Chayka points out that algorithms also pressure content creators, like musicians and artists, to tailor their work to fit these digital platforms. For instance, musicians on Spotify or TikTok might focus on creating catchy hooks at the beginning of their songs to grab the listener’s attention.
Despite the strong presence of these algorithms, Chayka believes that regulation could reduce their influence. He suggests that if Meta, the parent company of Facebook, were required to separate its various services, like Instagram or WhatsApp, and make them compete with each other, it could give users more control and choice over their digital consumption.
In summary, the change from simple, time-ordered social. media posts to algorithm-driven content has a big impact on both the viewers and the creators, influencing what we see, hear, and even think. Chayka’s insights highlight the need for greater awareness and potentially more regulation in our increasingly digital world.
12. According to the text, how have social media platforms changed in the past ten years?
A.They show posts in a time-based order. |
B.They prioritize posts from friends and family. |
C.They make adjustments to satisfy users’ needs. |
D.They provide more content to meet different needs. |
13. What does Kyle Chayka think of algorithmic recommendations?
A.They make users more active consumers. |
B.They shape users’ preferences and behaviors. |
C.They reduce the influence of content creators. |
D.They expose users to diverse and challenging content. |
14. How do algorithms influence musicians’ work on digital platforms?
A.By encouraging musicians to create longer songs. |
B.By discouraging musicians from using catchy hooks. |
C.By giving musicians more control and choice over their music. |
D.By requiring musicians to create their work to fit the platforms. |
15. What can be concluded from the text?
A.Tech companies should have more departments. |
B.Social media algorithms give content creators less opportunities. |
C.Social media algorithms flatten our culture by making decisions for us. |
D.Network platforms have increased the common recommendations for 10 years. |