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Monitoring youth depression risk in Web 2.0

Monitoring youth depression risk in Web 2.0 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png VINE: The Journal of Information and Knowledge Management Systems Emerald Publishing

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References (22)

Publisher
Emerald Publishing
Copyright
Copyright © 2009 Emerald Group Publishing Limited. All rights reserved.
ISSN
0305-5728
DOI
10.1108/03055720911003969
Publisher site
See Article on Publisher Site

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.

Journal

VINE: The Journal of Information and Knowledge Management SystemsEmerald Publishing

Published: Aug 28, 2009

Keywords: Worldwide web; Data analysis; Suicide; Young adults; Depression; Social networks

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