Utilizing artificial intelligence to make a prediction about an entity based on user sentiment and transaction history

A device, comprising:

• one or more memories;
• and
• one or more processors communicatively coupled to the one or more memories, configured to:
• receive comment information associated with a plurality of users and relating to an entity;
• generate a plurality of interim scores associated with the entity via artificial intelligence based upon the comment information;
• receive transaction information associated with one or more of the plurality of users,
• the transaction information relating to the entity;
• determine correlations between the plurality of interim scores associated with the comment information and the transaction information;
• generate a prediction about a future stock price of the entity based on the plurality of interim scores;
• store, in a relational database to reduce redundancy, the plurality of interim scores and the transaction information,
• the relational database being organized in columns and tables via a data normalization method;
• and
• cause an action to be taken based on the prediction about the future stock price of the entity,
• the action including one or more of:
• automatically provide, to a client device, a notification indicating the future stock price of the entity,
• automatically send an instruction to a server to buy or sell a stock associated with the entity, or
• automatically cause a calculation of a future value of a financial portfolio to be generated.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors, cause the one or more processors to:
• receive historical information associated with an entity;
• receive comment information associated with a plurality of users and relating to the entity;
• receive transaction information associated with one or more of the plurality of users,
• the transaction information relating to the entity;
• utilize artificial intelligence to calculate a plurality of interim scores for the entity based on the historical information and the comment information;
• determine correlations between the plurality of interim scores associated with the comment information and the transaction information by using at least one of:
• a correlation clustering method,
• a Pearson's product-moment coefficient method,
• an Anscombe's quartet method, or
• a Spearman's rank-correlation coefficient method;
• apply weights to the plurality of interim scores based upon the correlations;
• generate a prediction about a future stock price of the entity based on the weighted plurality of interim scores;
• store, in a relational database to reduce redundancy, the weighted plurality of interim scores and the transaction information,
• the relational database being organized in columns and tables via a data normalization method;
• and
• cause an action to be taken based on the prediction about the future stock price of the entity,
• the action including one or more of:
• automatically provide, to a client device, a notification indicating the future stock price of the entity,
• automatically send an instruction to a server to buy or sell a stock associated with the entity, or
• automatically cause a calculation of a future value of a financial portfolio to be generated.