What Does People Also Viewed Mean On Linkedin

Short Answer

The 'People Also Viewed' section on LinkedIn is an algorithmic recommendation feature that suggests similar profiles to users. It is based on shared professional traits, industry patterns, and collective browsing behavior.

Complete Explanation

The “People Also Viewed” section on LinkedIn is a recommendation engine located on the side panel of a user’s profile. It displays a list of other LinkedIn members that the platform’s algorithm deems relevant to the person whose profile is currently being viewed.

  • Algorithmic Basis: The feature operates on collaborative filtering. If a large number of users who visit Profile A also frequently visit Profile B, the system creates a link between them and suggests Profile B to others visiting Profile A.
  • Similarity Metrics: The algorithm considers shared attributes such as job titles, industry sectors, geographic locations, and educational backgrounds to determine relevance.
  • Dynamic Nature: The list is not static; it updates in real-time based on changing user traffic patterns and profile updates.

History / Background

LinkedIn introduced recommendation features as part of its evolution from a simple digital resume repository to a comprehensive professional social network. The “People Also Viewed” functionality is based on the same principles of data association used by e-commerce giants like Amazon (e.g., “Customers who bought this also bought…”). By leveraging big data and user behavior, LinkedIn aimed to increase the “stickiness” of the platform, encouraging users to spend more time exploring professional networks and discovering potential leads or candidates without needing to perform a manual search.

Importance and Impact

This feature significantly influences the discoverability of professional profiles. For job seekers, appearing in the “People Also Viewed” section of a high-profile industry leader can lead to increased organic profile views and recruitment opportunities. For recruiters, it serves as a discovery tool to find “lookalike” candidates who possess similar skill sets to a successful hire. However, it can also lead to unintended competition if a user is consistently grouped with their direct rivals in a specific niche.

Why It Matters

Understanding this feature allows users to optimize their profiles for better algorithmic placement. By using standardized job titles and industry-specific keywords, professionals can influence the likelihood of being associated with other influential figures in their field. It provides a glimpse into how the professional community perceives their role and positioning relative to peers, effectively acting as a mirror of their professional “cluster” within the global economy.

Common Misconceptions

Myth

The list is manually curated by the profile owner.

Fact

The “People Also Viewed” list is entirely automated by LinkedIn’s algorithm; users cannot choose who appears in this section.

Myth

It only shows people the user is already connected to.

Fact

The section frequently displays 2nd and 3rd-degree connections, or even total strangers, based on professional similarity rather than existing relationships.

FAQ

Can I remove myself from someone else's 'People Also Viewed' list?

No, users cannot manually remove themselves from these lists as they are generated by an automated algorithm based on global traffic patterns.

Does appearing in this list mean I am being compared to those people?

Algorithmically, yes. It indicates that the platform views your professional profile as similar in context or utility to the others listed.

How can I improve who appears in my 'People Also Viewed' section?

While you cannot control it directly, optimizing your profile with accurate industry keywords and standard job titles helps the algorithm categorize you more accurately.

References

  1. LinkedIn Help Center - Profile Visibility
  2. LinkedIn Engineering Blog - Recommendation Systems
  3. Professional Networking Best Practices Guide
  4. Digital Marketing Analysis of Social Algorithms
  5. User Interface Design Patterns for Social Networks

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