How LinkedIn uses AI and community experts for content creation

Seo March 15, 2024
On this page
  1. How Collaborative Articles Succeeds
  2. How LinkedIn Produced 10 Million Pages of Expert-Level Content
  3. LinkedIn's Innovations in Collaborative Articles: Elevating Content Quality and SEO Impact
  4. Key Insights for SEO

In just one year, LinkedIn's Collaborative Articles feature has achieved a milestone, surpassing 10 million pages of expert content. The project has witnessed a remarkable surge in weekly readership, escalating by over 270% since September 2023. Their journey to these milestones and plans for further advancements provide insightful lessons on crafting an SEO strategy that seamlessly integrates AI with human expertise.

How Collaborative Articles Succeeds

The rationale behind the success of Collaborative Articles lies in recognizing that individuals often seek information online to grasp subject matter topics. However, the internet doesn't always provide the most reliable insights from genuine subject matter experts. Typically, users conduct Google searches and may stumble upon platforms like Reddit, where information is posted without assurance of expertise. It's challenging for non-experts to discern whether content from anonymous individuals is trustworthy.

The solution to this dilemma was to harness LinkedIn's pool of experts to create articles within their areas of expertise. These articles rank on Google, providing a dual benefit: establishing credibility for the subject matter expert and incentivizing them to produce more content.

How LinkedIn Produced 10 Million Pages of Expert-Level Content

LinkedIn locates subject matter experts and reaches out to them to compose an essay on a given topic. The essay topics are generated using an AI "conversation starter" tool developed by LinkedIn's editorial team. These conversation topics are then paired with subject matter experts identified through LinkedIn's Skills Graph.

The LinkedIn Skills Graph links LinkedIn members to their subject matter expertise using a framework called Structured Skills. This framework employs machine learning models and natural language processing to identify related skills beyond those explicitly listed by members themselves.

This mapping process utilizes skills extracted from members' profiles, job descriptions, and other textual data on the platform as a foundation. AI, machine learning, and natural language processing are then employed to identify additional subject matter expertise that members may possess.

LinkedIn's Innovations in Collaborative Articles: Elevating Content Quality and SEO Impact

LinkedIn's Collaborative Articles project employs a strategic approach that yields millions of pages of top-tier content authored by subject matter experts across a vast array of topics. This might explain why LinkedIn's pages are increasingly prominent in Google search results.

LinkedIn is now enhancing its Collaborative Articles project with features designed to further elevate the quality of its pages.

  • Revised Questioning Approach: LinkedIn now presents subject matter experts with real-world scenarios to which they can respond with essays addressing pertinent topics and questions.
  • Introduction of a New Unhelpful Button: Readers now have the option to provide feedback to LinkedIn if they find a particular essay unhelpful. It's noteworthy, particularly from an SEO perspective, that LinkedIn frames the thumbs-down button within the context of helpfulness.
  • Enhanced Topic Matching Algorithms: LinkedIn has refined its methods for matching users with topics through what they term "Embedding Based Retrieval for Improved Matching," which aims to address member feedback concerning the quality of topic-to-member matching.

LinkedIn explains:

“Based on feedback from our members through our evaluation mechanisms, we focused our efforts on our matching capabilities between articles and member experts. One of the new methods we use is embedding-based retrieval (EBR). This method generates embeddings for both members and articles in the same semantic space and uses an approximate nearest neighbor search in that space to generate the best article matches for contributors.”

Key Insights for SEO

LinkedIn's Collaborative Articles project stands out as an exceptionally well-planned content creation endeavor, uniquely blending AI and machine learning with human expertise to produce trustworthy and valuable content that resonates with readers. 

Currently, LinkedIn leverages user interaction signals to enhance the quality of invited subject matter experts for article creation, while also identifying articles that fail to meet user needs.

The advantages of article creation extend beyond content quality improvement; every time an article by a high-quality subject matter expert ranks on Google, it serves as a promotional platform for showcasing skills, expertise, and authority, benefiting those promoting services, products, seeking clients, or pursuing career opportunities.