13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects.
13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. 14. The computer-readable storage medium of claim 13 , wherein establishing the dialect parameters comprises: identifying content items associated with one or more specified locations identified as correlated to a dialect.