@InProceedings{abdyusof-lin-guerin:2017:DDDSM,
  author    = {Abd Yusof, Noor Fazilla  and  Lin, Chenghua  and  Guerin, Frank},
  title     = {Analysing the Causes of Depressed Mood from Depression Vulnerable Individuals},
  booktitle = {Proceedings of the International Workshop on Digital Disease Detection using Social Media 2017 (DDDSM-2017)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {9--17},
  abstract  = {We develop a computational model to
	discover the potential causes of depression
	by analysing the topics in a usergenerated
	text. We show the most prominent
	causes, and how these causes evolve
	over time. Also, we highlight the differences
	in causes between students with low
	and high neuroticism. Our studies demonstrate
	that the topics reveal valuable clues
	about the causes contributing to depressed
	mood. Identifying causes can have a significant
	impact on improving the quality of
	depression care; thereby providing greater
	insights into a patient’s state for pertinent
	treatment recommendations. Hence, this
	study significantly expands the ability to
	discover the potential factors that trigger
	depression, making it possible to increase
	the efficiency of depression treatment.},
  url       = {http://www.aclweb.org/anthology/W17-5802}
}