The Influence of User Behavior vs. Algorithms on Online Polarization

# Stanford Scientist Argues It’s Not Algorithms Driving Polarization. It’s This Human Behavior

1. **”Echo chambers” and “filter bubbles”** are the main ways online platforms influence what content users see. Echo chambers occur when users actively seek information that confirms their beliefs, while filter bubbles emerge through algorithmic curation based on users’ previous behaviors.

2. **Users’ own choices and behaviors** play a more significant role in their exposure to partisan or unreliable news on Google Search than algorithmic curation. The study suggests that motivated behaviors drive users’ engagement with biased content, rather than the platform’s algorithms.

3. The study’s findings are specific to **Google Search**, and further research is needed to understand the impact of algorithmic curation on other news sites and media platforms. Future studies will explore how online information consumption affects people’s behaviors and attitudes on various platforms.

## Supplemental Information โ„น๏ธ

The study discussed in the article focuses on the influence of online platforms, particularly Google Search, on users’ exposure to biased and unreliable news. It challenges the common assumption that algorithmic curation is the primary driver of polarization and suggests that users’ own behaviors and choices play a more substantial role. Understanding the impact of algorithmic curation and user behavior is crucial for addressing the issue of polarization online.

### ELI5 ๐Ÿ’

People’s behavior, not just algorithms, affects what news they see online. Online platforms can create “echo chambers” when people look for information that confirms what they already believe, and “filter bubbles” when platforms show content based on what users have previously liked or clicked. A study found that users’ own choices, rather than algorithms, determine their exposure to biased news on Google Search. The study focused on Google, so more research is needed to understand other platforms.

#### Source ๐Ÿ“š:

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