PREDOSE

Goal

To determine user knowledge attitudes and behavior related to the non-medical use of Pharmaceutical Opioids To determine temporal trends and patterns in drug abuse

People

PIs: Raminta Daniulaityte, Amit P. Sheth Co-Investigators: Robert Carlson, Russel Falck Students: Delroy Cameron, Sujan Udayanga

Project Description

This research project aims to develop a mechanism to automate 'qualitative coding' in social research by automatically extracting triples from web data, particularly web forum posts. The goal of such triple extraction is to provide a framework that can be exploited to study user knowledge, attitudes and behaviors as it relates to non-medical use of pharmaceutical opiods (e.g. OxyContin, buprenorphine etc). Interesting areas include 1) Social Network analysis, intended to determine information diffusion patterns and 2) Spatial-Temporal-Thematic analysis, intended to determine trends within the community regarding usage, distribution, of method of administration of pharmaceutical opioids (including Suboxone and Subutex, which are buprenorphine products).

Architecture

Fig1: Citar project Architecture

Publications

N/A

Funding

This project is sponsored by NIH R21 Grant Award No. DA030571-01A1 to the Ohio Center for Excellence in Knowledge-enabled Computing (Kno.e.sis) and the Center for Treatment, Interventions and Addictions Research (CITAR) titled “A Study of Social Web Data on Buprenorphine Abuse using Semantic Web Technology.” Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Co-PIs: Amit P. Sheth and Raminta Daniulaityte. Co-Investigators: Russel Falck and Robert Carlson.

Contact: Delroy Cameron