Abstract: A computer-implemented method includes gathering data samples into a data set, correcting for imbalance in the data set to produce a corrected data set by applying active learning to the data set to increase a number of double barreled question data samples occurring in the data set, selecting an optimal machine learning model for the corrected data set, training the optimal machine learning model using the corrected data set, operating the optimal machine learning model on new data to produce a prediction result, and generating a visual representation of at least one prediction results.

Abstract: A method of filtering an original set of user-provided text responses across a network, including receiving, from one or more processors on one or more user computers, multiple user-provided text responses to a question, the multiple user-provided text responses forming the set, identifying text responses that are no-value text responses and removing the no-value text responses from the original set, removing text responses from the original set where the length of the response does not meet a threshold length, identifying text responses that are gibberish responses and removing gibberish responses from the original set, sending the remaining responses as a filtered set of responses to a machine learning system, the machine learning system to: perform clustering on the filtered set to identify one or more clusters of text responses that are similar to each other, identifying text responses outside the one or more clusters as noise responses, scoring the noise responses, and removing text responses having a sc

Abstract: A system can include a question repository to store multiple sets of questions, each set of questions including questions that may have a superficial, semantic, or open-ended modifier portion. A survey management module can allow a user to select a set of questions from the question repository for an online survey. A benchmarking module can group questions by semantic modifier options and provide an analysis based on information about the survey-creator and other survey-creators.