Getting a new friend suggestion notification on social media platforms like Facebook or LinkedIn means that the site’s algorithm has identified someone you may know and want to connect with. This is based on various factors like shared connections, networks, education, workplaces, interests, and more. While it doesn’t necessarily mean you have to send them a friend request, it’s a way for the platform to make connections between users who are likely to know each other. Let’s explore this notification further.
How Social Media Friend Suggestions Work
When you join a social media site, you start building connections by adding friends, joining groups, following interests, listing education and work details, etc. The site collects all this data about you and the people you connect with. Using sophisticated algorithms, it analyzes these details to identify patterns and potential mutual connections. For example:
- You went to the same high school as John Doe 5 years apart. The algorithm identifies this commonality and suggests John to you.
- Jane Doe works at the same company as you. The algorithm picks up this workplace connection and suggests Jane.
- You and Bob Doe have 15 mutual friends. The algorithm detects you share a strong friend overlap and suggests Bob.
As you continue adding more info and connections to your profile, the algorithm keeps refining its suggestions to surface people you’re very likely to know in real life. Other factors like location, age, gender, interests, group memberships etc. also influence suggestions.
Data used for friend recommendations
Here are some of the specific data points social platforms utilize for their friend recommendation algorithms:
- Education info – Schools, colleges, degrees etc.
- Workplaces
- Location and geographic data
- Mutual friends and connections
- Interests, pages, and groups
- Age and gender
- Interactions like comments, likes, shares etc.
- Networks and communities
- Shared posts and multimedia
- Language and cultural aspects
The more comprehensive your profile, the better algorithms can match you to relevant people. However, they also consider privacy settings – connections are only suggested if both sides have open profiles.
Why You Get Friend Suggestions
There are a few key reasons social platforms take the effort to identify potential friends and generate suggestions:
1. Help you connect with people you know
The main goal is to help you find and connect with acquaintances, old classmates, distant relatives, former colleagues, and others you already know but aren’t linked to on social media. Suggestions aim to bridge these gaps and grow your network.
2. Drive engagement
When you get recommendations of real-life connections, you’re more likely to send a request and interact with them. This boosts user engagement for the platform.
3. Provide value
Friend suggestions have utility as they help you reconnect with old connections. Users perceive value in platform features that add real value.
4. Compile more data
As you connect with more people, the platform gains additional data about you and your extended network. This can be used to improve ad targeting, analytics, and other revenue streams.
Types of Friend Recommendations
While most suggestions are of people you likely know, some may be strangers who share interests, networks, etc. Let’s look at the key types of friend recommendations:
1. People You May Know
The most common type, these are suggestions of acquaintances from your real-life social and professional circles – former classmates, colleagues, relatives, neighbors, mutual friends etc.
2. Based on Networks
People in your college alumni network, professional industry, social clubs, etc. Even if you don’t know them, you share common networks.
3. Location-based
People who live/work near you or visit your city frequently. Proximity is the basis of connection here.
4. Interests-based
Strangers who share similar hobbies, interests, fan pages, groups, etc. Platforms analyze your activities to find like-minded people.
5. Demographic-based
People with similar age, language, education, relationship status and other demographic traits as you. Algorithms look for aligned stats.
What to Do With Friend Suggestions
When you receive a new connection suggestion, here are some things you can do:
Accept if you know the person
If it’s someone you know, sending them a friend request helps you reconnect. Nurture real relationships.
Ignore if it’s irrelevant
You’re under no obligation to add strangers or vague acquaintances. Skip irrelevant ones.
Review mutual connections
Clicking on a suggestion shows your shared connections. This provides context into how you’re linked.
Check for shared interests
Beyond connections, see what interests, groups, pages etc. you have in common. This indicates compatibility.
Consider their profile and posts
Quickly glance through their profile and updates. This gives insights into their character and interests.
Limit interactions with strangers
Be cautious about accepting friend requests from people you have no offline connection with.
How to Refine Friend Suggestions
If you’re receiving many irrelevant recommendations, here are some ways to improve them over time:
Update your profile details
Add your education, job, location, contact info and ensure they are current. This provides more signal.
Join relevant groups and networks
Joining alumni, industry, interest-based groups and networks gives more for algorithms to work with.
Follow relevant pages and entities
Curate who you follow based on interests. Remove old/irrelevant follows.
Limit public posts
Post less publicly and more to specific groups and friends. This reduces irrelevant visibility.
Review privacy settings
Restrict certain profile fields and posts from public view. Lock down things you only want connections seeing.
Remove contacts
Unfriend or unfollow people you no longer interact with regularly or share few common contacts.
Report bad recommendations
Use platform tools to report irrelevant suggestions so they improve over time.
Turn off friend suggestions
Some platforms allow you to disable suggestions temporarily or permanently if you find them disruptive.
Risks of Accepting Friend Requests
While most recommendations are harmless, be vigilant about these risks when accepting requests:
Oversharing with strangers
Accepting strangers can lead to oversharing personal or professional updates with unknown people.
Security and privacy
Scammers and spammers often use friend requests for phishing attacks, hacking, spam, fraud etc.
Stalkers and harassment
Persistent friend requests could be a sign of stalking or harassment, especially from strangers.
Inappropriate content
Some connections may share objectionable, graphic or unethical content on timelines you can view.
Annoying interactions
You may get annoying messages, tags, and notifications from people you hardly know.
Reputation and credibility
Associating with certain people can damage your reputation and credibility, personal or professional.
Maintaining connections
Having too many friends or followers can become overwhelming to maintain interactions with.
Conclusion
Friend suggestions on social media are based on algorithms that analyze your profile, network, activities, and other data points to identify potential connections. While most suggestions will be of people you know, some may be strangers who share interests, networks or demographics. Consider mutual friends, interactions, profile compatibility and reputation of the person before accepting requests. Stay vigilant of risks like spam, oversharing, and inappropriate content. Use platform tools mindfully to refine suggestions and safeguard your privacy. Focus on nurturing real relationships, rather than just accumulating connections. Handle friend suggestions thoughtfully to grow your social circle while protecting your boundaries.
| Type | Basis | Risks |
|---|---|---|
| People You May Know | Mutual connections | Oversharing, stalking |
| Networks | Alumni, industry networks | Inappropriate content |
| Location | Living/working near you | Security and privacy issues |
| Interests | Similar hobbies and interests | Spam and phishing |
| Demographic | Age, education, status etc. | Annoying interactions |
This table summarizes the key types of friend suggestions, what they are based on, and some of the risks to be aware of when accepting different requests.
How to Respond to Friend Suggestions
When you get a friend suggestion notification, here are some recommended ways to respond:
- Accept – If it’s someone you know personally, reconnect by accepting the request.
- Ignore – You can ignore the notification and do nothing if it’s irrelevant.
- Review Profile – Check their profile, posts, interests etc. to gauge compatibility.
- Check Connections – See what mutual friends or networks you share.
- Research Person – Do an online search to learn more about a potential connection.
- Politely Decline – You can decline a request from someone you don’t wish to connect with.
- Limit Info Sharing – Be selective about what personal info or access you provide new friends.
- Enhance Privacy – Adjust your privacy settings and share less publicly.
- Report User – Report suspicious users to the platform admins for review.
The right response depends on who the suggestions are and what factors you consider important. Focus on building meaningful relationships online.
Examples of Friend Suggestions
To understand this better, here are some example friend recommendation scenarios and how you can interpret them:
Mutual Friends
“Jenny Young – You have 15 mutual friends.”
Here, the high friend overlap indicates you likely know Jenny through your shared connections, even if you’ve never met her before. Reviewing mutual friends can jog your memory.
University Network
“Alex Lee – Went to University of Florida.”
Alex shares your alumni network, though he graduated a few years before/after you. As fellow alumni, you have a connection via your education background.
Professional Industry
“Sarah Thomas – Works at Deloitte.”
Sarah works in the same industry as you, though not the same company. Your common professional domain connects you.
Geographic Location
“Nina Jones – Lives in Boston, Massachusetts.”
Nina lives in/often visits the same location as you. Your shared city provides a geographic connection.
Interests
“Matt Kim – Interested in Photography and Travel.”
Matt’s interests match your hobbies and fan pages. Your similar interests are the basis for suggestion.
Demographics
“Michelle Lee – Studied at NYU, from California.”
Michelle’s background and demographics like education, hometown, age etc. align with yours.
Common Concerns
Here are answers to some common concerns people have about friend suggestions:
Too many friend suggestions
Limit public info, tighten privacy settings, remove contacts to improve relevance. You can also disable suggestions.
Accepted a bad connection
Unlike adding direct contacts, you can remove friend suggestions from your friends list if they turn out inappropriate or irrelevant.
Suggestions from suspicious accounts
Report the account to platform admins. Avoid accepting requests from sketchy looking profiles.
Suggestions of former romantic partners
This can happen if you have many mutual connections. You can ignore them or block the user from viewing your profile.
Suggestions of dead connections
Algorithms may surface people who have passed away if others still actively engage with their profile. Report these to remove.
Finds suggestions disruptive
Most platforms allow you to turn off friend recommendations temporarily or permanently so you stop seeing them.
Wants higher quality suggestions
Filling out your profile fully and comprehensively helps surface better, more relevant recommendations over time.
In Summary
Friend suggestion notifications utilize data about your connections, networks, location, interests, and more to recommend new people to connect with on social media. Consider mutual friends, profile details, networks, interests, and reputation before accepting requests. Accept people you know to rekindle connections, but be vigilant of oversharing with strangers, spam risks, inappropriate content, and other concerns. Refine privacy settings and be selective about who you connect with online. Focus on building meaningful relationships rather than accumulating connections with random people. Handle friend suggestions thoughtfully to get value but also protect your boundaries.