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One of the most powerful yet often overlooked changes in mass media is the rise of algorithm-driven content. Platforms like TikTok and YouTube no longer rely on users to search for content; instead, they deliver personalized feeds based on user behavior. This has fundamentally changed audience expectations, as people now expect content to be curated specifically for them without having to actively seek it out. This shift reflects broader changes in digital media, where personalization and behavioral targeting play a central role in shaping user experiences (Jain & Purohit, 2022; Filak, 2021).
This shift has had a major influence on social culture. Algorithms shape not only what people see, but also how they think, what trends they follow, and even what opinions they form. From my experience, it’s easy to see how quickly content can become repetitive or tailored to specific interests, reinforcing certain perspectives while limiting exposure to others. This creates what many refer to as a “filter bubble,” where users are consistently exposed to content that aligns with their existing preferences, reinforcing patterns of selective exposure and engagement (Jain & Purohit, 2022).
Culturally, this has made media consumption both more personalized and more fragmented. Instead of shared media experiences, audiences now exist in individualized content ecosystems. While this increases engagement and relevance, it also raises concerns about bias, misinformation, and the long-term impact on how society forms collective understanding, particularly as digital platforms prioritize content that aligns with user behavior rather than diverse or balanced perspectives (Filak, 2021).
References
Jain, S., & Purohit, H. C. (2022). Consumer acceptance of online behavioural advertising: Role of persuasion knowledge and protection motivation. International Management Review, 18(2), 48–54.
Filak, V. F. (2021). Convergent journalism: An introduction (4th ed.). Taylor & Francis.
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