TY  - JOUR
PY  - 2021//
TI  - Applying text mining methods to suicide research
JO  - Suicide and life-threatening behavior
A1  - Cheng, Qijin
A1  - Lui, Carrie S. M.
SP  - 137
EP  - 147
VL  - 51
IS  - 1
N2  - OBJECTIVE: To introduce the research methods of computerized text mining and its possible applications in suicide research and to demonstrate the procedures of applying a specific text mining area, document classification, to a suicide-related study. <br><br>METHOD: A systematic search of academic papers that applied text mining methods to suicide research was conducted. Relevant papers were reviewed focusing on their research objectives and sources of data. Furthermore, a case of using natural language processing and document classification methods to analyze a large amount of suicide news was elaborated to showcase the methods. <br><br>RESULTS: Eighty-six papers using text mining methods for suicide research have been published since 2001. The most common research objective (72.1%) was to classify which documents exhibit suicide risk or were written by suicidal people. The most frequently used data source was online social media posts (45.3%), followed by e-healthcare records (25.6%). For the news classification case, the top three classifiers trained for classification tasks achieved 84% or higher accuracy. <br><br>CONCLUSIONS: Computerized text mining methods can help to scale up content analysis capacity and efficiency and uncover new insights and perspectives for suicide research.<p />  <p>Language: en</p>
LA  - en
SN  - 0363-0234
UR  - http://dx.doi.org/10.1111/sltb.12680
ID  - ref1
ER  -