Detect negative event for depression tendency from web blogs

Chia Ming Tung, Wen Hsiang Lu

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Many negative events happened in short period of time would trigger depressive disorder. We categorized these negative events into four groups, which are Family, Study, Jobs, and Affection. In this paper, we try to identify negative event in the web blog posts through proposed Enhanced Event Extraction method that includes Enhanced Lexicon Feature, POS pattern, and event-emotion pair. Term frequency and length had been used to calculate importance score for a long negative term in Enhanced Lexicon Feature. In POS pattern, we combined multiple POS term as negative event pattern, such VC+Nh, VC+Na, P+VC. We also consider about the distance between event terms and emotion terms. If emotion terms could be labeled in a post, we could use distance relationship to find event around emotion term. Experimental results show that the accuracy rate of Enhanced Event Extraction method is 54.9%.

原文English
主出版物標題The 15th International Conference on Biomedical Engineering, ICBME 2013
編輯James Goh
發行者Springer Verlag
頁面801-804
頁數4
ISBN(電子)9783319029122
DOIs
出版狀態Published - 2014
事件15th International Conference on Biomedical Engineering, ICBME 2013 - Singapore, Singapore
持續時間: 2013 12月 42013 12月 7

出版系列

名字IFMBE Proceedings
43
ISSN(列印)1680-0737

Other

Other15th International Conference on Biomedical Engineering, ICBME 2013
國家/地區Singapore
城市Singapore
期間13-12-0413-12-07

All Science Journal Classification (ASJC) codes

  • 生物工程
  • 生物醫學工程

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