TREND IDENTIFICATION AND MODIFICATION RECOMMENDATIONS BASED ON INFLUENCER MEDIA CONTENT ANALYSIS

摘要

Metadata of influencer media content from content platforms are analyzed, a potential product is identified, and attributes for the potential product is extracted. Profile data of followers of the influencer is obtained, and the followers are clustered. An influence factor of the influencer is calculated for each cluster. The followers in the clusters are ranked based on interactions with the influencer. A potential media content related to the potential product is identified, and a placement recommendation to a given cluster is provided based on the influence factors for the clusters and on the follower ranks. Potential future trends are identified based on information related the influencer and are thus predictive and forward-looking, instead of reactive and backward-looking. The potential media contents and the strategic placement of the potential media contents leverages the anticipation of a trend due to the activities of the influencer.