Social Web Data on Buprenorphine Abuse

Using Semantic Web Technology

The non-medical use of pharmaceutical opioids has been identified as one of the fastest growing forms of drug abuse in the United States. There is a critical need to enhance current epidemiological monitoring, early warning and post-marketing surveillance systems by providing additional and more timely data. The World Wide Web has been identified as one of the “leading edge” data sources for detecting patterns and changes in drug use practices. Many web sites provide a venue for individuals to freely share their own experiences, post questions and offer comments about different drugs. Such user generated content (UGC) can be used as a very rich data source to study knowledge, attitudes and behaviors related to illicit drugs.

This National Institute on Drug Abuse-funded study is a collaborative effort between researchers at CITAR and the Center for Knowledge-Enabled Information Services and Science (Kno.e.sis) at Wright State University. Its goal is to apply cutting-edge information processing techniques, such as the Semantic Web, Natural Language Processing (NLP), and Machine Learning, to qualitative and quantitative content analysis of web-based UGC to achieve the following aims:

  1. Describe drug users’ knowledge, attitudes and behaviors related to the illicit use of Suboxone® (buprenorphine and naloxone) and Subutex® (buprenorphine);
  2. Identify and describe spatial and temporal patterns of illicit use of these drugs as reflected on web-based forums.

The study will generate new information about the practices of buprenorphine abuse and will contribute to the advancement of public health and substance abuse research by providing automatic coding and information extraction tools needed to handle rapidly growing web-based data. The automated information extraction methods applied in this study could enhance current early warning and epidemiological surveillance systems as well as contribute to the development of web-based interventions.

Staff Contact Information

Publications

  • Daniulaityte, R., Carlson, R.G., Falck, R.S., Cameron, D., Perera, S., Chen, L., Sheth, A. (2012) "I just wanted to tell you that loperamide WILL WORK": A web-based study of extra-medical use of loperamide.  Drug Alcohol Depend, 130(I-3):241-4. [Abstract]