A statistical algorithm-driven digital system is provided for automated optimization of a large number of key performance indicators (KPI) involved in social digital interactions among users, contents and advertisement, further augmented by data-driven verification and recommendation. Users include humans from diverse socio-cultural-economic groups, whose identity may be pseudonymous, whose explicit features may remain private, though statistically imputable. Contents include webpages, downloads, videos, music, or content accessed by users. Advertisements include product placement, branding, appeal, surveys, or other third-party contents, not explicitly sought by user. Application executing on server digital device responds to requests received from client devices for delivering requested digital content, customizes selected piece of digital content delivered to client application (in response to request) based on ordinal rankings for users, contents and advertisements, computed by tensor based algorithm. Rankings computed are predictive of user's future social interactions, as determined by past statistical data, summarized in sparse high-dimensional tensors.
RANK, CLUSTER, CHARACTERIZE AND CUSTOMIZE USERS, DIGITAL CONTENTS AND ADVERTISEMENT CAMPAIGNS BASED ON IMPLICIT CHARACTERISTIC DETERMINATION