Facebook’s “People You May Know” feature suggests new friends based on several factors. The algorithm looks at mutual friends, networks, workplaces, schools, geographical locations, and other connections to determine who to recommend. Here’s a quick overview of how it works:
- Mutual friends – If you and another person have several friends in common, you’ll likely be suggested to each other.
- Networks – People in the same Facebook groups or networks as you may show up as suggestions.
- Workplaces – Co-workers at the same company are often recommended.
- Schools – Classmates and alumni from the same schools are suggested.
- Location – People who live in your area or frequently visit places near you may appear.
- Contacts – If you upload your contact list, Facebook will match it against existing members.
- Cookies/tracking – Facebook uses browser cookies and web tracking methods to suggest people you’ve visited off of Facebook.
The algorithm behind “People You May Know” is complex and constantly evolving. But in general, the more connections two people share, the more likely Facebook will recommend them to connect.
The Evolution of “People You May Know”
Facebook launched the “People You May Know” feature in 2008 as a way to connect users with friends of friends. Since then, it has become a core part of the Facebook experience. Here is a brief timeline of how PYMK has evolved over the years:
2008 – Initial launch of PYMK, relying primarily on mutual friend connections.
2009 – PYMK starts factoring in networks, workplaces, and schools.
2011 – Location data from smartphones enables PYMK to suggest nearby acquaintances.
2012 – Facial recognition technology allows PYMK to match profile photos, even without metadata tags.
2014 – PYMK expands to consider people you’ve interacted with across the web via cookies and tracking methods.
2016 – Machine learning models help improve ranking and relevance of PYMK suggestions.
2018 – Additional data points like events, Pages liked, and posts viewed help the algorithm suggest new connections.
2020 – PYMK adds shortcuts to message, follow, or add friends directly from the recommendations.
Over a decade later, PYMK is more integral to the Facebook experience than ever, using ever-advancing technology to recommend new connections.
Ranking Factors
Facebook uses machine learning models to rank and select the most relevant people to suggest in PYMK. While the exact algorithms are proprietary, these key factors likely impact who Facebook recommends:
- Number of mutual friends – More shared friends means a higher ranking.
- How recently a new mutual friend was added – A new connection may increase a suggestion’s ranking.
- Whether you’ve interacted on Facebook – Liking, commenting on, or sharing the same content can boost suggestions.
- Physical proximity – People nearby more frequently rank higher.
- Shared networks – Common group membership influences rankings.
- Education and workplaces – Alumni and coworkers tend to see each other in PYMK.
In addition to ranking existing connections higher, Facebook’s algorithm also seeks out “second-degree” suggestions – friends of your friends who you may share offline connections with.
Limiting Suggestions
Too many PYMK suggestions or recommendations of people you’d rather not connect with? Here are some ways to limit or tailor who Facebook recommends:
- In PYMK, choose “See fewer suggestions” on people you aren’t interested in connecting with.
- Go to Settings > Privacy > Use the “Limit Past Posts” tool to reduce what PYMK sees.
- Restrict old posts and profiles so only friends can see them.
- Be cautious about liking Pages, joining public groups, and connecting multiple social media accounts.
- If you want to limit professional contacts, use Lists to segregate friends from coworkers.
Reducing your overall Facebook activity can also decrease unwanted PYMK suggestions. But often the best solution is curating your friends list and being selective about posting personal information publicly.
Importance for Businesses
PYMK isn’t just about connecting with old classmates. Many businesses also leverage Facebook’s suggestion algorithm. Here are some of the key benefits for companies:
- Increasing brand reach by getting Page or profile suggestions out to more potential customers.
- Building a targeted custom audience for ads based on People Who Like your Page and their friends.
- Driving more conversions by retargeting people who’ve already engaged with your brand.
- Staying top of mind by resurfacing old leads in “Suggested for You” ads.
- Remarketing to past customers who previously showed interest.
Savvy marketers use PYMK to extend their audience. But brands should also be aware that overly-aggressive marketing via PYMK can annoy users. Maintaining a balance is key.
Privacy Concerns
The data Facebook uses to power PYMK has raised some privacy concerns over the years. Critics argue:
- PYMK relies on gathering large amounts of personal information without full user consent.
- Suggestions may reveal connections or relationships users don’t necessarily want known.
- Facebook’s tracking of activity off-platform feels invasive to some users.
- Users have limited control over opting out of PYMK suggestions.
- Young users may not fully grasp how their information is used for PYMK.
Facebook maintains that users have control over their experience via privacy settings. But PYMK does demonstrate the breadth of data Facebook harnesses to influence connections. Users should be aware of this.
The Future of PYMK
What’s next for People You May Know? A few potential innovations:
- More integration with Facebook Dating to suggest potential romantic matches.
- Tighter Links with Facebook Pay and commerce partners to serve deals.
- Feb 21 2023 Expansion to Facebook’s VR spaces as the metaverse evolves.
- Harnessing AI to craft more “serendipitous” suggestions.
- New controls over types of suggestions users receive.
But the core goal will remain the same – harnessing data to help users find new connections. PYMK will continue adapting to new platforms and technologies to drive engagement through friend recommendations.
Conclusion
Facebook’s “People You May Know” feature has become a pillar of its platform, using sophisticated algorithms and data signals to suggest new connections. While users have some control to limit suggestions, PYMK demonstrates how extensively Facebook maps relationships across digital and real-world activity.
Businesses also benefit from PYMK’s ability to target audiences and resurface old leads. But brands should be careful not to overdo outreach through suggestions. As PYMK continues evolving, Facebook must strike a balance between enabling connections and respecting user privacy.