MENTAL DISORDERS OVER TIME:

A DICTIONARY-BASED APPROACH TO THE ANALYSIS OF KNOWLEDGE DOMAINS

Inna Kouper, Angela Zoss, Trevor Edelblute, Michael Boyles, Hamid EkbiaIndiana University, Duke University

March 21, 2016

Visualizing PubMed

Research Questions

RQ1: What types of mental disorders received research attention at different times?RQ2: What specific terms are used within certain topical areas?RQ3: How does terminology change within topical areas change over time?

Method

Method (cont.)

Method (cont.)■ Developed and used a Python classifier to match keywords

in titles and dictionary■ Matched within a window of +2 words■ Retained all matches for multiple disorders in a title■ Aggregated and visualized results

Findings – Overall trends

Findings – Case 1, Autism

Findings – Case 2, Intellectual disabilities

Findings – Case 3, Gender disorders

Conclusion

■ Combination of dictionary work, natural language processing and visualization enables the analysis of historical trends in knowledge domains

■ Results are useful in raising awareness of term persistence and of systemic preferences for certain areas in research

■ This is just the beginning…– Interactivity– Rule-based classification– Multilingual processing– More data sources