Using Machine Learning to Design the Match-Up System between Influencers and Products

Abstract

Due to the mature of internet and the rise of the media in these years, online marketing has become a trend to increase the visibility. The traditional marketing methods have been replaced by social media gradually. With the sharing and recommendation of influencers on the social platform, a wider response than traditional marketing can be obtained. Therefore, this research will implement two systems, named the influencer crawler system and the match-up system between influencers and products. First, to obtain the information of influencers in social media through the influencer crawler system, use text mining technology to extract useful information from these social media interactive data, and then use machine learning to matchmaking influencers and products. We use questionnaires to verify and understand the public's expectations for the matchmaking of Influencers and products.