1. To determine user knowledge attitudes and behavior related to the non-medical use of pharmaceutical opioids (namely buprenorphine) as discussed on Web-based forums
2. To determine spatio-temporal trends and patterns in pharmaceutical opioid abuse as discussed on Web-based forums

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

Problem: Historically, qualitative research has been characterized by manual data collection, initiated by interactive interview sessions with individual or a group of individual addicts. The audio-to-text transcribed interviews obtained from this process are then typically annotated by researchers/experts with themes or topics that surfaced during interview sessions. This process is called qualitative coding. Various tools, such as ... have been developed to facilitate this annotation process, and provide additional service such as search, retrieval and data analysis. However, the intensive manual effort required to make the interactive approach scalable is enormous. Furthermore, to effectively process the large volume and complexity of the Web-based data, the field certainly needs a highly automated way of accessing and processing Web data.

Proposed Solution: Researchers at the Kno.e.sis Center at Wright State University have successfully applied Semantic Web, Machine Learning and Natural Language Processing techniques to automatically extract knowledge from biomedical text. Substantial progress has also been made in using these and other techniques to understand the content and identify social perceptions through metadata extraction and spatio-temporal and thematic analysis (broadly termed semantic analysis) of informal text on MySpace, Facebook, and Twitter. These cutting-edge information processing techniques, with appropriate adaptations can now be exploited to fit the needs of public health and drug abuse research.

The overall research plan has three(3) distinct stages: the first stage is the Data Collection stage, which is an intended alternative to manually conducted interviews. It operates under the assumption that information gathered from interview sessions are expressed in online forums and therefore, data crawling software can be used to collect data from web sources instead of laborious interviews as the means of obtaining qualitative data. The second stage is the process of Automatic Qualitative Coding. Through entity identification, relationship identification and complete triple extraction, this process aims at capturing the semantics of information expressed in the web forum data, with acceptable levels of precision and recall. The complete range of techniques, including pattern-based, statistical probabilistic and semantics-based analysis will play a critical role in this phase. The final stage is Data Analysis & Interpretation of the RDF data (i.e. Drug Abuse Ontology - DOA) collected from phase 2 using existing semantic web tools at Kno.e.sis or new tools to be developed where appropriate.