Analysis of Twitter data for postmarketing surveillance in pharmacovigilance

Pain, Julie, Levacher, Jessie, Quinqunel, Adam and Belz, Anja (2016) Analysis of Twitter data for postmarketing surveillance in pharmacovigilance In: Proceedings of the 2nd Workshop on Noisy User-generated Text, Osaka, Japan, 11 Dec 2016.

[img] Text
W16-39 (1).pdf - Published Version

Download (1MB)

Abstract

Postmarketing surveillance (PMS) has the vital aim to monitor effects of drugs af- ter release for use by the general pop- ulation, but suffers from under-reporting and limited coverage. Automatic meth- ods for detecting drug effect reports, es- pecially for social media, could vastly in- crease the scope of PMS. Very few auto- matic PMS methods are currently avail- able, in particular for the messy text types encountered on Twitter. In this paper we describe first results for developing PMS methods specifically for tweets. We de- scribe the corpus of 125,669 tweets we have created and annotated to train and test the tools. We find that generic tools per- form well for tweet-level language iden- tification and tweet-level sentiment anal- ysis (both 0.94 F1-Score). For detection of effect mentions we are able to achieve 0.87 F1-Score, while effect-level adverse- vs.-beneficial analysis proves harder with an F1-Score of 0.64. Among other things, our results indicate that MetaMap seman- tic types provide a very promising ba- sis for identifying drug effect mentions in tweets.

Item Type: Contribution to conference proceedings in the public domain ( Full Paper)
Additional Information: © Copyright of each paper stays with the respective authors (or their employers).
Subjects: G000 Computing and Mathematical Sciences > G700 Artificial Intelligence > G710 Speech & natural language processing
G000 Computing and Mathematical Sciences > G700 Artificial Intelligence > G760 Machine Learning
Depositing User: Converis
Date Deposited: 21 Apr 2017 12:29
Last Modified: 21 Apr 2017 12:35
URI: http://eprints.brighton.ac.uk/id/eprint/16837

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year