“Proof-of-Influence” is an algorithm that uses machine learning to analyze the big data extracted from influencers social networks to identify their followers and the main subjects that they cover and produce an Inflr Score TM , which measures the reach or level of engagement of the influencer.
Inflr Score
One of the biggest challenges of influence marketing is determining a coherent value for influencer remuneration that matches their actual engagement in social networks. Inflr Score is a number from 0 to 100 that represents the proven engagement of an influencer with his/her followers. This score is used to assign a monetary value to the posts of the influencer on each social network.
Inflr categorizes influencers using artificial intelligence, which identifies the main subjects of posts, photos, and videos, (such as ”applying makeup” or “playing football”) and can even analyze the emotional context of a post by detecting facial expressions in images. The algorithm also helps identify potentially unsafe or inappropriate content in images and videos.
The makeup of an influencer’s audience in their social networks is identified using a machine learning algorithm, which analyzes videos, photos, posts, and profiles of followers. Faces in pictures and videos are analyzed to determine attributes such as gender, age group, and ethnicity. The geographical location of an influencer’s audience is determined via geolocation obtained from followers who interact with the posts generated by the campaigns within the platform.
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