How to Protect Yourself on Social Media
Recommendation algorithms shape nearly everything we see online. While in some cases they are helpful, they can also impact our opinions and behavior. Understanding what data is collected and how it is used is essential to protecting yourself as a consumer of social media content.
How Platforms Gather Data
More data is fed to content recommendation algorithms than most users realize. While we might know that explicit interactions (likes, comments, reposts, follows) contribute to our recommendations, there are other types of data that we often don’t even realize are being gathered.
Explicit interactions give a good picture of what content you enjoy, but sometimes engagement is not just measured by direct interaction. Information like how long you look at a post and how many times you rewatch a video are implicit interactions. Sometimes, implicit interactions can be even more valuable data because it is hard to fake. While you may watch and enjoy a video, you might not like it if your likes are publicly available, but the amount of time you spend looking at something doesn’t lie.
Platforms may also collect contextual and personal data. This includes, but is not limited to:
- Type of Device (laptop, phone)
- Device Brand (iPhone, Android)
- Operating System (Windows, Mac, Linux)
- Current Location (approximate or precise)
- Location History
- IP Address
- Time of Day
- Language Settings
- Full Name
- Home Address
- Contact Information (phone, email)
How Platforms Use Data
We already discussed that this data can be used to inform content recommendation algorithms, but it also has other uses. Not only do social media companies buy information about you to use in their algorithms, they may also sell this information to third parties and data brokers. They also use this data in targeted advertising, which creates the majority of their revenue.
Platforms like Facebook claim they don’t sell user data. However, this isn’t the full story. Most companies sell access to user data by allowing advertisers to target audiences based on their behavior patterns. Even if user data is not sold directly, it is still being monetized.
