Table 4.

Summary of statistical and machine learning methods and data sources for pharmacovigilance using Twitter data.

Public Health Issue	Method	Complementary Data
Smoking	Bayesian Logistic Regression [62]
HIV	Support Vector Machine [63], Word2Vec [28], Doc2Vec [28], Multilayer Perceptron [63], Decision Tree [63], Dynamic Topic Modeling [28]
Vaccination	Semantic Network Analysis [87]
Drug Abuse	Decision Tree [65], Support Vector Machine [58], Topic Model [66], Simple Statistical Analysis [88]	National Surveys on Drug Usage and Health (NSDUH)
Adverse Drug Reactions (ADRs)	Conditional Random Field [85,89], Lexicon Analysis [89,90], Deep Learning (RNN) [86], Word Embeddings (Glove) [86], Word2Vec [85]	ADRMine
Adverse Drug Events (ADEs)	Multi-Instance Logistic Regression (Milr) [69], Semi-Supervised Multi-Instance (Nssm) [91], Bayesian Inference [83], Support Vector Machine [83,92], Lexicon Analysis [92]
Alcoholism	Simple Statistical Analysis [84]
Miscellaneous	Decision Tree [93], Support Vector Machine [94], Latent Dirichlet Allocation [94]