Patent ID: 11968414
Assignee: nan
Field: Audio-visual technology (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 0:
1. A method for predicting who will be watching a television program, the method comprising:
reviewing text related to the program, the text comprising: plot information, sub-title information, summary information, script information, or synopsis information, or any combination thereof;
determining pre-determined genre words and pre-determined keywords correlating to ratings based on machine learning analysis of historical information comprising: historical ratings data, historical scheduling data, or content contextual data, or any combination thereof;
determining which words from the text are relevant words, the relevant words being words that help identify genre words or keywords;
determining how closely the relevant words coincide to the pre-determined genre words by generating a breakdown of how many relevant words are the pre-determined genre words and the pre-determined keywords; and
using a machine learning model to train a neural network using data sets to: predict who will watch the program based on the breakdown and by evaluating audience social engagement using a buzz algorithm, wherein the buzz algorithm comprises:
determining web site visit information by searching pre-determined web site sources for identifying information, the identifying information comprising: an Internet Movie Database (IMDB) identifier, an official hashtag, an official program name, or any combination thereof; and counting how many times a day the identifying information is mentioned in the pre-determined web site sources;
determining social media mention information;
determining user commentary sentiment scoring information;
determining regional source relevancy information;
determining time shift information comprising time shift reason information, time decay information, and original airing or original release information; and
performing a carryover analysis on the program to determine an impact of a previous program on whether persons will continue to watch a related program.