STC: A Joint Sentiment-Topic Model for Community Identification

Baoguo Yang; Suresh Manandhar

doi:10.1007/978-3-319-13186-3_48

STC: A Joint Sentiment-Topic Model for Community Identification

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	Undefined/Unknown
Title of host publication	Trends and Applications in Knowledge Discovery and Data Mining
Subtitle of host publication	PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers
Publisher	Springer
Pages	535-548
Number of pages	14
ISBN (Electronic)	978-3-319-13186-3
ISBN (Print)	978-3-319-13185-6
DOIs	https://doi.org/10.1007/978-3-319-13186-3_48
Publication status	Published - 2014

Access to Document

10.1007/978-3-319-13186-3_48

Cite this

Yang, B., & Manandhar, S. (2014). STC: A Joint Sentiment-Topic Model for Community Identification. In Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers (pp. 535-548). Springer. https://doi.org/10.1007/978-3-319-13186-3_48

Yang, Baoguo ; Manandhar, Suresh. / STC : A Joint Sentiment-Topic Model for Community Identification. Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers. Springer, 2014. pp. 535-548

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title = "STC: A Joint Sentiment-Topic Model for Community Identification",

author = "Baoguo Yang and Suresh Manandhar",

year = "2014",

doi = "10.1007/978-3-319-13186-3_48",

language = "Undefined/Unknown",

isbn = "978-3-319-13185-6",

pages = "535--548",

booktitle = "Trends and Applications in Knowledge Discovery and Data Mining",

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Yang, B & Manandhar, S 2014, STC: A Joint Sentiment-Topic Model for Community Identification. in Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers. Springer, pp. 535-548. https://doi.org/10.1007/978-3-319-13186-3_48

STC: A Joint Sentiment-Topic Model for Community Identification. / Yang, Baoguo; Manandhar, Suresh.
Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers. Springer, 2014. p. 535-548.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yang B, Manandhar S. STC: A Joint Sentiment-Topic Model for Community Identification. In Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers. Springer. 2014. p. 535-548 doi: 10.1007/978-3-319-13186-3_48