Citation

Goh TT, Huang YP. VINE 2009; 39(3): 192-202.

Copyright

(Copyright © 2009)

DOI

10.1108/03055720911003969

PMID

unavailable

Abstract

PURPOSE Social networking sites have in recent years become an increasingly popular avenue for young people to express and to share their thoughts, views, and emotions. When young people are emotionally distressed for instance, instead of the traditional channel of consulting friends, parents or specialists, social networking blogs may provide a channel to share and release their emotions and intentions. The objective of the paper is to explore the use of text mining and data warehousing technologies to identify and monitor bloggers who are depressed and may be at risk of suicide, self harm or harming others.

DESIGN/METHODOLOGY/APPROACH The paper first provides a literature review on relevant work in affective and emotional content text mining and relevant suicide research. An algorithm based on a weighted dictionary text search algorithm was developed to identify at risk bloggers to illustrate the viability of the system. An example that compares the percentage of at-risk bloggers of three different countries - Australia, the UK and New Zealand-- from a sample blog population is provided.

FINDINGS The results show that it is possible to use text mining technologies to identify depressed bloggers. However, there is a need for future research to improve identification and remove false alarms. Practical implications The ability to identify at-risk bloggers and to provide appropriate interventions could be critical in avoiding tragic consequences. Such a system could provide an e-monitoring service for various social agencies to engage with potentially at-risk bloggers.

ORIGINALITY/VALUE The current research represents pioneer work in monitoring depression risk in weblogs - research on monitoring at-risk bloggers is rather limited. © 2009, Emerald Group Publishing Limited

Language: en

Keywords

Research; Literature reviews; Depression; Suicide; Young adults; Algorithms; Social networks; Worldwide web; Data reduction; World Wide Web; Blogs; Data analysis; Data mining; Data warehouses; Design/methodology/approach; False alarms; Natural language processing systems; Social networking (online); Social networking sites; Young peoples