conftrace_

2018 EMNLP EMNLP 2018

Dealing with Medication Non-Adherence Expressions in Twitter

Abstract

AbstractThrough a semi-automatic analysis of tweets, we show that Twitter users not only express Medication Non-Adherence (MNA) in social media but also their reasons for not complying; further research is necessary to fully extract automatically and analyze this information, in order to facilitate the use of this data in epidemiological studies.

Authors

Takeshi Onishi, Davy Weissenbacher, Ari Klein, Karen O’Connor, Graciela Gonzalez-Hernandez

Topics

Artificial Intelligence > Core AI > Causal Inference Machine Learning > Core Methods > Classification

Keywords

text classification named entity recognition medication adherence twitter mining

More from EMNLP 2018

All EMNLP 2018 papers →

Changes in Psycholinguistic Attributes of Social Media Users Before, During, and After Self-Reported Influenza Symptoms

Thumbs Up and Down: Sentiment Analysis of Medical Online Forums

Identification of Emergency Blood Donation Request on Twitter

Detecting Tweets Mentioning Drug Name and Adverse Drug Reaction with Hierarchical Tweet Representation and Multi-Head Self-Attention

Classification of Medication-Related Tweets Using Stacked Bidirectional LSTMs with Context-Aware Attention

Shot Or Not: Comparison of NLP Approaches for Vaccination Behaviour Detection