Influencer Lookalikes: A Novel Approach to Identifying Similar Social Media Users

As brand marketing budgets increasingly focus on partnering with social content creators, selecting the appropriate talent to align with their brand becomes increasingly critical. This research paper focuses on presenting a novel technique for finding similar users, or ”social lookalikes,” in order to better identify partners. The system’s faster speed and interpretability are also significant in this process. The novel technique employs the core concepts of semi-supervised learning, i.e., clustering and embedding methodology. The advanced methodology is evaluated using a specially designed numerical validation technique. The method has the capability to deliver a set of similar social profiles and similar promotional performers with reasonably low variance.