Methods, systems, and computer-readable media for evaluating the quality of text within online advertisements using output from a language model are provided. The output from the language model may be used by a machine-learning algorithm to generate a quality score for an individual advertisement. The quality score may be used to filter out advertisements with poor text quality or to tax or penalize an advertisement within an online auction. The ad quality scores may also be used to rank or score advertisers that submit the ads. In one embodiment, the advertiser's quality score is combined with an individual ad's quality score to create a final score, which is used to evaluate the advertisement. The advertiser rank/score and ad quality score may be communicated to an advertiser as advertiser feedback.
展开▼