1. A method performed by at least one computer processor, the method comprising: (A) searching a first dataset for elements matching inclusion set criteria to identify an inclusion set, wherein the inclusion set comprises a first subset of the first dataset; (B) searching the dataset for elements matching exclusion set criteria to identify an exclusion set, wherein the exclusion set comprises a second subset of the first dataset; (C) identifying a set of unique content elements selected from the inclusion set and the exclusion set; (D) sorting the set of unique content elements to produce a sorted set of unique content elements; (E) filtering, from the sorted set of unique content elements, all but the first N elements in the sorted set of unique content elements to produce a filtered set of unique content elements; (F) excluding at least one content element from the filtered set of unique content elements to produce a final set of unique content elements; and (G) producing a predictive model based on the final set of unique content elements; wherein (D) comprises, for each of the unique content elements E: (D)(1) identifying a percentage IP of records in the inclusion set containing element E; (D)(2) identifying a percentage EP of records in the exclusion set containing element E; (D)(3) identifying an absolute value |IP−EP| of a difference between IP and EP; and (D)(4) sorting the set of unique content elements in descending order by the absolute value |IP−EP| of the unique content elements in the set of unique content elements to produce the sorted set of unique content elements.