Have you ever opened LinkedIn to find a suggestion to connect with someone from your distant past—perhaps an old flame or a brief acquaintance—leaving you wondering, "How on earth did LinkedIn know about this person?" You're not alone in this puzzling experience.

LinkedIn's connection recommendation system often feels like it has access to parts of your life you never intended to share on a professional networking site. Understanding how these suggestions work can help you navigate the platform more effectively and protect your privacy.

The Mystery Behind "Based on Your Profile" Suggestions

Many LinkedIn users have experienced the unsettling moment when the platform suggests connections that seem to come from their personal rather than professional lives.

"100% of the people that were listed as 'Based on your profile' (and nothing else) on my LinkedIn were women I dated in the last few years who were not connected to me professionally," shared one Reddit user, highlighting a common concern.

Another user expressed similar confusion: "Some random guy I dated 6 years ago just showed up 'based on my profile' and I don't understand how. He's not even in my contacts anymore."

These experiences raise important questions about how LinkedIn's algorithm works and what data it uses to generate these surprisingly personal suggestions.

How LinkedIn's Connection Algorithm Actually Works

LinkedIn's "People You May Know" feature relies on several key factors to suggest potential connections:

1. Network Degrees and Mutual Connections

The most straightforward aspect of LinkedIn's suggestion algorithm involves your existing network:

• First-degree connections: People you're directly connected to

• Second-degree connections: People connected to your first-degree connections

• Third-degree connections: People connected to your second-degree connections

The more mutual connections you share with someone, the more likely they'll appear in your suggestions.

2. Contact Syncing and Email Integration

A major source of those seemingly mysterious connection suggestions comes from contact syncing features:

• Email contacts: If you've ever allowed LinkedIn to scan your email contacts (Gmail, Outlook, etc.)

• Mobile phone contacts: If you've granted LinkedIn access to your phone's contact list

• Other users' contacts: Even if you haven't shared your contacts, if someone else has your information in their synced contacts, you might appear in each other's suggestions

This explains why that "random guy" from years ago might suddenly appear—if they have your contact information saved and have synced their contacts with LinkedIn.

3. Profile Views and Platform Activity

Your behavior on LinkedIn also influences who appears in your suggestions:

• Profile views: LinkedIn often suggests people whose profiles you've viewed or who have viewed yours

• Similar profile attributes: Those with similar work experiences, skills, education, or industries

• Engagement patterns: People who interact with the same content you do or participate in the same groups

4. Algorithm Learning and Pattern Recognition

LinkedIn's algorithm continuously learns from user behavior across the platform:

• It analyzes which suggestions users accept versus ignore

• It identifies patterns in successful connections to improve future recommendations

• It uses machine learning to refine its understanding of professional relationships

Privacy Implications and Data Sharing Concerns

The personal nature of some LinkedIn suggestions has raised legitimate privacy concerns among users. One Reddit user noted, "It seems like social media has been sharing information. People from dating apps are showing up as suggestions on my personal profile on Facebook."

While LinkedIn officially states that it doesn't scan private messages for suggestions, several pathways exist for personal connections to appear in your recommendations:

1. Cross-platform data: Though LinkedIn denies directly sharing data with other platforms, many users connect multiple accounts using the same email address or phone number, creating digital breadcrumbs

2. Contact import features: When any user imports their contacts, it affects suggestions for everyone in that contact list

3. Third-party integrations and cookies: Various apps and websites may share data that eventually influences LinkedIn's algorithm

Managing Your Connection Suggestions

If you're uncomfortable with LinkedIn's connection suggestions, you can take several steps to regain control:

Review and Adjust Your Privacy Settings

LinkedIn provides several options to manage how your data is used for recommendations:

1. Go to your LinkedIn Privacy settings

2. Look for "Syncing options" and "Connections" settings

3. Disable contact syncing features if you haven't already

4. Manage how your profile data is used for recommendations

Be Mindful of Contact Sharing

• Avoid syncing your phone or email contacts with LinkedIn if privacy is a concern

• Remember that even if you don't share contacts, others might have your information in their contacts

• Regularly review the permissions you've granted to LinkedIn's mobile app

Use "Remove" on Unwanted Suggestions

When you see a suggestion you don't want:

• Click the "X" or "Remove" option on the suggestion

• This not only removes that specific suggestion but helps the algorithm learn your preferences

Beyond Connections: The Broader LinkedIn Algorithm

LinkedIn's algorithm extends beyond just connection recommendations. It also determines what content appears in your feed and how your own posts perform. Understanding these mechanisms can help you maximize your professional networking experience.

Content Visibility and the "Golden Hour"

When you post content on LinkedIn, the algorithm evaluates it through several phases:

1. Initial quality check: LinkedIn first screens content for spam, policy violations, or low-quality indicators

2. The critical "Golden Hour": The first hour after posting is crucial for determining visibility

"If no one sees your post or interacts with it in the first hour... well... rest in peace to that post," explains one marketer on Reddit. This initial engagement period heavily influences whether your content reaches a broader audience.

Quality Over Quantity

LinkedIn's algorithm favors thoughtful content over high-volume posting. As one Reddit user advised, "Don't spam your followers, please." The algorithm can detect patterns associated with low-quality content, including:

• Excessive posting frequency

• Low engagement rates

• Repetitive content

• Poor grammar and formatting

How This Affects Your Professional Networking

Understanding LinkedIn's algorithm helps you build more meaningful connections and avoid awkward suggestions. By being intentional about your LinkedIn activity, you can:

1. Curate a truly professional network: By manually searching and connecting with relevant professionals rather than relying solely on algorithm suggestions

2. Protect your privacy: By understanding and managing how your data is used for recommendations

3. Increase your content visibility: By engaging strategically during the critical first hour after posting

How Kondo Can Help Manage LinkedIn Connections

For professionals who use LinkedIn extensively for networking and business development, managing the influx of connection requests and messages can become overwhelming. This is where tools like Kondo can make a significant difference.

Kondo helps you organize LinkedIn communications by introducing labels and split inboxes, allowing you to categorize conversations based on their relevance and priority. This is particularly useful when you receive connection requests from suggested contacts that may not immediately fit into your professional circle but could be valuable later.

With Kondo's reminder feature, you can snooze conversations with new connections until the appropriate follow-up time, ensuring you don't lose track of potentially valuable professional relationships amid the clutter of LinkedIn's sometimes puzzling recommendations.

Frequently Asked Questions

Why does LinkedIn suggest people I know personally but not professionally?

LinkedIn suggests personal acquaintances primarily due to contact syncing. If you or the other person has ever synced email or phone contacts with LinkedIn, and that contact information exists, LinkedIn's algorithm may identify this as a potential connection, even if there's no direct professional link on the platform.

What data does LinkedIn primarily use for its connection suggestions?

LinkedIn primarily uses data from your network degrees (1st, 2nd, 3rd degree connections), synced contacts from email or phone, your profile information (like work experience, skills, education), and your activity on the platform (profile views, engagement with content).

How can I stop LinkedIn from suggesting my personal contacts?

You can reduce unwanted personal suggestions by managing your privacy settings. Specifically, navigate to LinkedIn's "Syncing options" and "Connections" settings to disable or remove synced email and phone contacts. Also, be mindful of granting contact access to the LinkedIn mobile app.

Does LinkedIn use my private messages to make connection suggestions?

No, LinkedIn officially states that it does not scan your private messages to generate connection suggestions. Suggestions are typically based on shared connections, contact imports, profile similarities, and platform activity rather than private message content.

How does my activity on LinkedIn influence the connections suggested to me?

Your activity, such as viewing profiles, the profiles you engage with, and the groups you join, significantly influences suggestions. LinkedIn's algorithm learns from these interactions, often suggesting people whose profiles you've viewed, who have viewed yours, or who share similar professional interests and engagement patterns.

What is the "Golden Hour" on LinkedIn and why is it important for my posts?

The "Golden Hour" refers to the first hour after you publish a post on LinkedIn. This period is critical because the initial engagement (likes, comments, shares) your post receives heavily influences whether LinkedIn's algorithm will show it to a broader audience or limit its reach.

Conclusion

LinkedIn's connection suggestion algorithm works through a complex combination of network analysis, contact data, profile similarities, and user behavior. While this system aims to help you expand your professional network, it sometimes produces suggestions that feel surprisingly personal or disconnected from your professional life.

By understanding how these recommendations work and taking steps to manage your privacy settings, you can maintain better control over your LinkedIn experience and build a network that truly supports your professional goals.

Remember that LinkedIn's primary purpose is professional networking—so when those awkward suggestions from your distant past appear, you can now understand why they're there and how to manage them effectively.

Have you experienced unusual connection suggestions on LinkedIn? How do you manage your professional network on the platform? Share your experiences and strategies in the comments below.