Social Media-based Substance Use Prediction
Table 5: MUE: Prediction Results
['[EMPTY]', 'Tobacco', 'Alcohol', 'Drug']
We compared our multi-view learning results with 3 baselines: BestSPE and BestSLE are the best single view models. We also used a 3rd baseline called Unigram_combine, which simply concatenates all the post and like unigrams together and then applies supervised feature selection before uses the remaining features in a SVM-based classification. and DCCA significantly outperformed the unigram-based baseline (p<0.01 based on t-test). The difference between the best multi-view models (wGCCA_balanced for Alcohol and drug, wGCCA_imbalanced for drugs) and the best single view models are also significant (p<0.01). wGCCA also performed significantly better than DCCA on our tasks (p<0.01 based on t-tests).