HIGHLIGHTS
SUMMARY
The specific contribution of this study is the exploration of a machine_learning classifier for the collection and analysis of a large database of labeled comments that were written by internet users and collected from multiple public sources. The training data were then used to develop a machine_learning model that automated the classification process for large volumes of data (the modeling phase). The authors manually annotated a small percentage of the data (1174 of 203,219 comments) and designed a neural_network to classify the remaining comments. The training and testing data were compiled before all . . .
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