Ranking online advertisements using retailer and product reputations

A method for predicting a reputation for a retailer or a product or both, comprising:

• collecting one or more online reviews of the retailer or the product or both that are associated with an advertisement;
• determining a probability of a positive orientation and a probability of a negative orientation for each online review;
• determining an orientation for each online review by comparing the probability of the positive orientation with the probability of the negative orientation;
• and
• calculating the predicted reputation of the retailer or the product or both based on a percentage of online reviews with a positive orientation.

A computer system, comprising:

• a processor;
• and
• a memory comprising program instructions executable by the processor to:
• receive a query;
• determine a level of relevance between the query and one or more advertisements in a set of advertisements;
• select the advertisements having a level of relevance above a pre-determined level of relevance;
• retrieve a predicted reputation for a retailer and a predicted reputation for a product associated with each selected advertisement;
• calculate a ranking score for each selected advertisement based on the predicted reputation for the retailer and the predicted reputation for the product;
• and
• rank the selected advertisements based on the ranking score.