Filter Bubbles

Filter bubbles are created when algorithms personalize content for users based on their past behavior and preferences. This can lead to users only seeing content that is tailored to their interests, which can limit their exposure to new ideas and perspectives. This can lead to an echo chamber effect, where users are only exposed to content that reinforces their existing beliefs and opinions.

In this activity, you will try to uncover evidence of filter bubbles on online search portals (search engines, news portals, etc.).

Part 1: Search Engines

Search engines often use algorithms to personalize search results for users. Personalization algorithms are based on a variety of factors, including user geography, search history, and past behavior, the collection of which constitutes a user “profile”. This profile is used to tailor search results to a user’s preferences. It may also be used to target advertising to a user.

A potential drawback of personalization is that it potentially results in users only seeing content that match their past (or existing) interests.

Try the following experiment. You may want to work with a partner for this exercise, as different users have different profiles and may thus see different search results.

1. Pick a handful of search terms that you are interested in. Choose a range of topics, from politics, to current events, to retail, to local businesses.

2. Explore how search results vary across browsers. Search for these terms in the following search engines:
   • Google
   • DuckDuckGo

   What do you notice about the differences in the search results? Are there any differences that you find surprising? Are any aspects of Google’s that you could imagine are tailored based on your past behavior on Google products? (Note that DuckDuckGo does personalize results based on your current profile, such as your geography, but does not perform tracking or history.)

3. Repeat the above experiment, but do your best to alter your profile in certain ways. For example, you might try one or more of the following:
   • Logged out of your Google account
   • Incognito mode
   • From Tor browser
   • Using a VPN to change your geographic location
   • From your phone
4. Repeat the above experiment (Steps 1-3) with other platforms that perform personalization. One idea to try would be the Google news portal. You might also try other platforms that perform personalization (e.g., Amazon).

Part 2: Discussion

1. What are some of the potential benefits of personalization? What are some of the potential drawbacks?
2. Is it ethical for social media companies to manipulate users’ news feeds to create filter bubbles?
3. What is the potential role of media literacy in mitigating the effects of filter bubbles?
4. To what extent do individuals have control over their own filter bubbles, and how can they actively seek out diverse perspectives?