Abstract: A computer-implemented method may include: receiving, by a first computer server, content provider data and content item data; identifying a plurality of profile elements by applying machine learning techniques to the received content provider data and content item data; calculating a first plurality of profile element scores for the content provider in each of the plurality of profile elements and a second plurality of profile element scores for the plurality of content items in each of the plurality of profile elements; determining, by utilizing one or more distance algorithms, profile element vector distances between the first plurality of profile element scores for the content provider and the plurality of second profile element scores for the plurality of content items; ranking the plurality of content items based on the determined profile element vector distances; and generating an interactive graphical user interface (GUI) displaying a plurality of radar graphs.

Abstract: A computer-implemented method may include: receiving, by a first computer server, content provider data and content item data; identifying a plurality of profile elements by applying machine learning techniques to the received content provider data and content item data; calculating a first plurality of profile element scores for the content provider in each of the plurality of profile elements and a second plurality of profile element scores for the plurality of content items in each of the plurality of profile elements; determining, by utilizing one or more distance algorithms, profile element vector distances between the first plurality of profile element scores for the content provider and the plurality of second profile element scores for the plurality of content items; ranking the plurality of content items based on the determined profile element vector distances; and generating an interactive graphical user interface (GUI) displaying a plurality of radar graphs.

Abstract: A computer-implemented method may include: receiving, by a first computer server, content provider data and content item data; identifying a plurality of profile elements by applying machine learning techniques to the received content provider data and content item data; calculating a first plurality of profile element scores for the content provider in each of the plurality of profile elements and a second plurality of profile element scores for the plurality of content items in each of the plurality of profile elements; determining, by utilizing one or more distance algorithms, profile element vector distances between the first plurality of profile element scores for the content provider and the plurality of second profile element scores for the plurality of content items; ranking the plurality of content items based on the determined profile element vector distances; and generating an interactive graphical user interface (GUI) displaying a plurality of radar graphs.

Abstract: The invention includes systems and methods for selecting and distributing content based on personality. The invention provides an insight generation tool that receives brand, audience, and content personalities and profile elements and determines and provides client and agency insights. Brand personality is matched with audience personality is matched with content personality. Profile elements of the brand, the audience, and the content are matched. Agency content and branded media content is identified, selected, and distributed, and is distributed over video distribution networks based on the relationship between the brand personality, the media content personality, and the audience personality. The invention improves the effectiveness of targeted advertising of media content providers by evaluating multiplatform content offerings and identifies content that has the closest personality.