LinkedIn’s Collaborative Articles features surpassed 10 million pages of expert content in a single year. The Collaborative Articles project’s weekly viewership has increased by more than 270% since September 2023. How they achieved these milestones and intend to achieve even greater outcomes provide helpful information for developing an SEO strategy that combines AI and human skills.
Why Collaborative Articles Work?
The Collaborative Articles project is based on the assumption that people use the Internet to learn about subject matter themes, but what is available on the Internet is only sometimes the most reliable information from subject matter experts.
A person often searches on Google and then goes to a site like Reddit to read what’s posted. Still, there’s no guarantee that the material is from a subject matter expert or the person with the greatest social media mouth. How can someone who is not a subject matter expert determine whether a post by a stranger is trustworthy and expert?
The idea was to use LinkedIn experts to generate articles on issues in which they are experts. The pages rank in Google, which benefits the subject matter expert and encourages him or her to generate more content.
How LinkedIn Created 10 Million Pages of Expert Content
LinkedIn recognizes subject area experts and contacts them to write an essay about the issue. A LinkedIn editorial team created an AI “conversation starter” tool that generates essay themes. These conversation topics are then linked to subject area experts identified by LinkedIn’s Skills Graph.
The LinkedIn Skills Graph connects LinkedIn users to subject matter knowledge using a framework called Structured Skills, which uses machine learning models and natural language processing to uncover similar talents beyond what the members clearly define.
The mapping begins with the abilities discovered in members’ profiles, job descriptions, and other text data on the site. Then it utilizes AI, machine learning, and natural language processing to expand on the members’ extra subject matter knowledge.
The Skills Graph description describes:
“If a member is familiar with Artificial Neural Networks, he or she is also familiar with Deep Learning, which is synonymous with Machine Learning.
Our machine learning and AI algorithms analyze large quantities of data to identify new capabilities and relationships.
We use natural language processing to extract skills from various text forms confidently. This ensures accurate mapping of abilities to members.”
Experience, Expertise, Authority, and Trustworthiness
LinkedIn’s Collaborative Articles initiative has a brilliant underlying concept that results in millions of pages of high-quality material written by subject matter experts on a wide range of topics. That may clarify why LinkedIn pages have become more visible in Google searches.
LinkedIn is upgrading its Collaborative Articles initiative with new features that aim to increase page quality even more.
- Changed how questions are asked: LinkedIn now presents scenarios to subject matter experts, who may reply with essays on real-world subjects and queries.
- New unhelpful button: There is now an option that users can use to notify LinkedIn that a certain essay is not helpful. It’s fascinating from an SEO viewpoint that LinkedIn is presenting the thumbs-down button through the lens of helpfulness.
- Improved Topic Matching Algorithms: LinkedIn has enhanced how they match people to subjects with what they call “Embedding Based Retrieval For Improved Matching,” which was built in response to member comments on the quality of topic-to-member matching.
LinkedIn explains,
“We concentrated our efforts on our matching skills between articles and member experts after receiving input from our members via our assessment tools. One of the new technologies we utilize is embedding-based retrieval (EBR). This technique creates embeddings for both members and articles in the same semantic space and then performs an approximate nearest neighbor search to find the best article matches for contributors.”
LinkedIn’s Collaborative Articles project is one of the most well-thought-out content development initiatives in recent years. What makes it not only outstanding is that it combines AI and machine learning technology with human skills to generate expert and useful information that readers like and can trust.
LinkedIn is now using user interaction signals to enhance the quality of subject matter experts asked to write articles, as well as to identify content that does not match users’ demands.
The benefits of writing articles include the promotion of high-quality subject matter experts every time their article ranks in Google, which allows anyone promoting a service, or product, or looking for clients or the next job to demonstrate their skills, expertise, and authoritativeness.
Source- searchenginejournal
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