Publication | Closed Access
Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets
16
Citations
3
References
2018
Year
Unknown Venue
Two-staged Annotation StrategyAbuse DetectionSubstance UseMachine LearningEngineeringSocial Medium MonitoringDeep Learning ModelJournalismText MiningNatural Language ProcessingComputational Social ScienceSocial MediaData ScienceConventional AnnotationAddiction MedicinePublic HealthSocial Medium MiningKnowledge DiscoveryDeep LearningTarget PredictionSubstance AbuseAddictionSocial Medium DataArts
Social media such as Twitter can provide urgently needed drug abuse intelligence to support the campaign of fighting against the national drug abuse crisis. We employed a targeted tweet collection approach and a two-staged annotation strategy that combines conventional annotation with crowdsourced annotation to produce annotated training dataset. In this demo, we share deep learning models trained in a boosting manner using the data from the two-staged annotation method and unlabeled data collection to detect drug abuse risk behavior in tweets.
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