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Investigating Major Topics Through the Analysis of Depression-related Facebook Group Posts

  • Journal of the Korean Society for Library and Information Science
  • 2019, 53(4), pp.171-187
  • DOI : 10.4275/KSLIS.2019.53.4.171
  • Publisher : 한국문헌정보학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : October 9, 2019
  • Accepted : November 19, 2019
  • Published : November 30, 2019

Yong-Jun Zhu 1 Dong Hun Kim 2 Changho Lee 2 YI, YONG JEONG 2

1성균관대학교
2성균관대학교 문헌정보학과

Excellent Accredited

ABSTRACT

The study aims to analyze the posts of depression-related Facebook groups to understand major topics discussed by group users. Specifically, the purpose of the study is to identify the topics and keywords of the posts to understand what users discuss about depression. Depression is a mental disorder that is somewhat sensitive in the online community, which is characterized by accessibility, openness and anonymity. The researchers have implemented a natural language-based data analysis framework that includes components ranging from Facebook data collection to the automated extraction of topics. Using the framework, we collected and analyzed 885 posts created in the past one year from the largest Facebook depression group. To derive more complete and accurate topics, we combined both automated and manual (e.g., stop words removal, topic size determination) methods. Results indicate that users discuss a variety of topics including depression in general, human relations, mood and feeling, depression symptoms, suicide, medical references, family and etc.

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