1. A computer-implemented method, comprising: providing a computing apparatus having a transaction handler configured in an electronic payment processing network connecting separate computers, including first computers controlling consumer accounts from which payments of transactions are made in the electronic payment processing network; second computers controlling merchant accounts in which the payments are received via the electronic payment processing network; and transaction terminals configured to initiate the transactions in the electronic payment processing network using identifications of the consumer accounts; a data warehouse coupled with the transaction handler and storing: first transaction data recording payment transactions processed by the transaction handler in a first period of time, and second transaction data recording payment transactions processed by the transaction handler in a second period of time; and a portal coupled with the data warehouse; receiving, in the portal of the computing apparatus using a communication channel outside the electronic payment processing network, internet content indicative of consumer sentiment during the first period of time; evaluating, by the computing apparatus, consumer sentiment values based on the internet content published during the first period of time; correlating, by the computing apparatus using a machine learning technique, the first transaction data recording the payment transactions processed by the transaction handler in the first period of time with the consumer sentiment values evaluated based on the internet content published during the first period of time; generating, by the computing apparatus, a computer quantification model of consumer sentiment from the correlating; training the computer quantification model based on adjusting parameters of the quantification model to reduce differences between the consumer sentiment values evaluated based on internet content published during the first period of time, and numerical values computed from applying the first transaction data in the first period of time to the quantification model; adjusting regional and temporal differences in emotional sentiment for the numerical values in the training of the quantification model; receiving, by the computing apparatus from the data warehouse, the second transaction data recording payment transactions of a group of users during the second period of time; applying, by the computing apparatus, the second transaction data to the quantification model; determining, by the computing apparatus through the applying of the second transaction data to the computer quantification model, a numerical value of consumer sentiment of the group of the users during the second period of time; identifying, by the computing apparatus, offers based at least in part on the numerical value of consumer sentiment of the group of the users; and communicating, by the portal using a channel outside the electronic payment processing network, the offers to the group of the users.