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postgraduate thesis: Automatic identification of hot topics and user clusters from online discussion forums

TitleAutomatic identification of hot topics and user clusters from online discussion forums
Authors
Advisors
Advisor(s):Chow, KPHui, CK
Issue Date2011
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Lai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995
AbstractWith the advancement of Internet technology and the changes in the mode of communications, it is found that much first-hand news have been discussed in Internet forums well before they are reported in traditional mass media. Also, this communication channel provides an effective channel for illegal activities such as dissemination of copyrighted movies, threatening messages and online gambling etc. The law enforcement agencies are looking for solutions to monitor these discussion forums for possible criminal activities and download suspected postings as evidence for investigation. The volume of postings is huge, for 10 popular forums in Hong Kong; we found that there are 300,000 new messages every day. In this thesis, we propose an automatic system that tackles this problem. Our proposed system downloads postings from selected discussion forums continuously and employs data mining techniques to identify hot topics and cluster authors into different groups using word based user profiles. Using these data, we try to locate some useful trends and detect crime from the data, the result is discussed afterward with include advantages and limitations of different approaches and at the end, there is a conclusion of the way to solve those problems and provide future direction of this research.
DegreeMaster of Philosophy
SubjectData mining.
Cluster analysis.
Dept/ProgramComputer Science

 

DC FieldValueLanguage
dc.contributor.advisorChow, KP-
dc.contributor.advisorHui, CK-
dc.contributor.authorLai, Yiu-ming.-
dc.contributor.author黎耀明.-
dc.date.issued2011-
dc.identifier.citationLai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995-
dc.description.abstractWith the advancement of Internet technology and the changes in the mode of communications, it is found that much first-hand news have been discussed in Internet forums well before they are reported in traditional mass media. Also, this communication channel provides an effective channel for illegal activities such as dissemination of copyrighted movies, threatening messages and online gambling etc. The law enforcement agencies are looking for solutions to monitor these discussion forums for possible criminal activities and download suspected postings as evidence for investigation. The volume of postings is huge, for 10 popular forums in Hong Kong; we found that there are 300,000 new messages every day. In this thesis, we propose an automatic system that tackles this problem. Our proposed system downloads postings from selected discussion forums continuously and employs data mining techniques to identify hot topics and cluster authors into different groups using word based user profiles. Using these data, we try to locate some useful trends and detect crime from the data, the result is discussed afterward with include advantages and limitations of different approaches and at the end, there is a conclusion of the way to solve those problems and provide future direction of this research.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.source.urihttp://hub.hku.hk/bib/B47849952-
dc.subject.lcshData mining.-
dc.subject.lcshCluster analysis.-
dc.titleAutomatic identification of hot topics and user clusters from online discussion forums-
dc.typePG_Thesis-
dc.identifier.hkulb4784995-
dc.description.thesisnameMaster of Philosophy-
dc.description.thesislevelMaster-
dc.description.thesisdisciplineComputer Science-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b4784995-
dc.date.hkucongregation2012-

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