At LinkedIn, trust is the cornerstone for building meaningful connections and professional relationships. Our members rely on us to create an environment on our platform where they can safely learn and grow in their careers. As part of this responsibility, we are constantly looking for innovative ways to prevent policy-violating behavior such as harassment, spamming, fake accounts, and other activities that undermine the positive and respectful interactions our community strives to uphold. By leveraging cutting-edge technologies, machine learning algorithms, and a dedicated team, we […]

Building Trust and Combating Abuse On Our Platform

Co-Authors: Shubham Agarwal and Rishi Gupta At LinkedIn, we work every day to deliver a safe and trusted experience for our members and customers. A key part of this work is our content abuse defense systems, which function behind the scenes to help detect and remove policy-violating content from the platform, while helping surface professional, relevant, and meaningful content that adds value to the member experience. We rigorously invest in enhancing these defense systems, which are a foundational pillar to maintaining member trust and safety and delivering a positive member […]

Enhancing Content Review: Proactively addressing threats with AutoML

Authors: Ryan Rogers, Subbu Subramaniam, Lin Xu Contributors: Mark Cesar, Praveen Chaganlal, Xinlin Zhou, Jefferson Lai, Jennifer Li, Stephanie Chung, Margaret Taormina, Gavin Uathavikul, Laura Chen, Rahul Tandra, Siyao Sun, Vinyas Maddi, Shuai Zhang Content creators post on LinkedIn with the goal of reaching and engaging specific audiences. Post analytics helps creators measure their post performance overall and with specific viewer demographics, so they can better understand what resonates and refine their content strategies. The number of impressions on each post shows how many […]

Privacy Preserving Single Post Analytics

Co-Authors: Abhishek Chandak and Ritish Verma We recognize that our 1 billion members and their over 10 billion years’ worth of collective knowledge and insights bring tremendous value to the LinkedIn community. That's why we're committed to enabling our members and customers to safely engage and connect with content. Our Trust & Safety team works diligently to keep harmful content off the platform, allowing members to tap into the real-life, meaningful insights and information shared by their peers. We do this through a multi-layer defense system that includes AI models, member […]

Augmenting our content moderation efforts through machine learning and dynamic content prioritization

On the LinkedIn platform, members from around the world share their knowledge, perspectives, and discuss topics important to them. Our goal at LinkedIn is to enable them to do so in a safe, trusted, and professional environment. We’ve previously discussed the various systems used to create a safe and trusted experience for our members and how we keep the LinkedIn Feed relevant for our members on LinkedIn. To provide a positive member experience, when content is posted or shared that goes against our LinkedIn Professional Community Policies, or when content is reported as violating […]

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