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Conference Paper: A hybrid system for online detection of emotional distress

TitleA hybrid system for online detection of emotional distress
Authors
KeywordsAffect mining
Blogs
Depression
Emotional distress
Hand-crafted model
Hybrid system
Machine learning
Public health
Issue Date2012
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 2012 Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2012), Kuala Lumpur, Malaysia, 29 May 2012. In Lecture Notes In Computer Science, 2012, v. 7299, p. 73-80 How to Cite?
AbstractNowadays, people are familiar with online communication and tend to express their deeper feelings on the Web. In the light of this situation, we present a hybrid system based on affect analysis for mining emotional distress tendencies from publicly available blogs to identify needy people in order to provide timely intervention and promote better public health. We describe the system architecture with a hand-crafted model at a fine level of detail. The model, which incorporates human judgment, enables the adjustment of prediction in machine learning on blog contents. The system blending supervised and unsupervised approaches will be examined and evaluated in lab experiments and practice. © 2012 Springer-Verlag.
DescriptionLNCS v. 7299 entitled: Pacific Asia Workshop, PAISI 2012 ... Proceedings
Persistent Identifierhttp://hdl.handle.net/10722/173568
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorLi, TMHen_HK
dc.contributor.authorChau, Men_HK
dc.contributor.authorWong, PWCen_HK
dc.contributor.authorYip, PSFen_HK
dc.date.accessioned2012-10-30T06:33:37Z-
dc.date.available2012-10-30T06:33:37Z-
dc.date.issued2012en_HK
dc.identifier.citationThe 2012 Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2012), Kuala Lumpur, Malaysia, 29 May 2012. In Lecture Notes In Computer Science, 2012, v. 7299, p. 73-80en_US
dc.identifier.isbn9783642304279-
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/173568-
dc.descriptionLNCS v. 7299 entitled: Pacific Asia Workshop, PAISI 2012 ... Proceedings-
dc.description.abstractNowadays, people are familiar with online communication and tend to express their deeper feelings on the Web. In the light of this situation, we present a hybrid system based on affect analysis for mining emotional distress tendencies from publicly available blogs to identify needy people in order to provide timely intervention and promote better public health. We describe the system architecture with a hand-crafted model at a fine level of detail. The model, which incorporates human judgment, enables the adjustment of prediction in machine learning on blog contents. The system blending supervised and unsupervised approaches will be examined and evaluated in lab experiments and practice. © 2012 Springer-Verlag.en_HK
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.subjectAffect miningen_HK
dc.subjectBlogsen_HK
dc.subjectDepressionen_HK
dc.subjectEmotional distressen_HK
dc.subjectHand-crafted modelen_HK
dc.subjectHybrid systemen_HK
dc.subjectMachine learningen_HK
dc.subjectPublic healthen_HK
dc.titleA hybrid system for online detection of emotional distressen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLi, TMH: timlmh@hku.hken_HK
dc.identifier.emailChau, M: mchau@hkucc.hku.hken_HK
dc.identifier.emailWong, PWC: paulw@hku.hk-
dc.identifier.emailYip, PSF: sfpyip@hku.hk-
dc.identifier.authorityChau, M=rp01051en_HK
dc.identifier.authorityWong, PWC=rp00591en_HK
dc.identifier.authorityYip, PSF=rp00596-
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/978-3-642-30428-6_6en_HK
dc.identifier.scopuseid_2-s2.0-84862172041en_HK
dc.identifier.hkuros207068-
dc.identifier.hkuros226667-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84862172041&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume7299en_HK
dc.identifier.spage73en_HK
dc.identifier.epage80en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridLi, TMH=7406372329en_HK
dc.identifier.scopusauthoridChau, M=7006073763en_HK
dc.identifier.scopusauthoridWong, PWC=55449317100en_HK
dc.identifier.scopusauthoridYip, PSF=7102503720en_HK
dc.customcontrol.immutablesml 130917-

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