Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32194
DC FieldValueLanguage
dc.contributorDepartment of Computing-
dc.contributorDepartment of Management and Marketing-
dc.creatorLiu, JNK-
dc.creatorWong, HK-
dc.creatorHu, Y-
dc.creatorNgai, EWT-
dc.creatorCho, VWS-
dc.date.accessioned2015-08-28T04:28:36Z-
dc.date.available2015-08-28T04:28:36Z-
dc.identifier.issn2307-9142-
dc.identifier.urihttp://hdl.handle.net/10397/32194-
dc.language.isoenen_US
dc.publisherMartin Science Publishingen_US
dc.subjectTwitteren_US
dc.subjectSocial networking serviceen_US
dc.subjectBehavior analysisen_US
dc.subjectSpammer detectionen_US
dc.titleModeling of social network services for deception detectionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage101-
dc.identifier.epage120-
dc.identifier.volume3-
dc.identifier.issue1-
dcterms.abstractSocial Networking Services (SNS) has become an important element of people’s daily lives. Users of SNS tend to send numerous messages and keep updating each other during engagement for information sharing. Meanwhile, however on the dark side, advertisers and malicious users are also attracted to it. The problem is getting more serious as the number of sites increases. Spam messages from advertisers and malicious users have been reported greatly annoying normal users. Accordingly, technologies referring to solve this problem is worth to be investigated.-
dcterms.abstractOur study mainly focuses on the second largest Social Network Site in the world, Twitter. In this paper, the interaction methods and types of relations would be reviewed first. Consequently, several features of deception behavior are identified. These features are then computerized and tested against real data. Results are analyzed and statistics are generated to reflect whether the features identified earlier effectively represent certain aspects of spammers’ behavior prevailing in recent time. Our investigation provides some hints on detecting spam on Twitter, and it is hoped that the outcomes of the study can provide rooms for improvement of anti-spam systems in future development.-
dcterms.bibliographicCitationInternational journal of information science and intelligent system, 2014, v. 3, no. 1, p. 101-120-
dcterms.isPartOfInternational Journal of Information Science and Intelligent System-
dcterms.issued2014-
dc.identifier.rosgroupidr72365-
dc.description.ros2013-2014 > Academic research: refereed > Publication in refereed journal-
Appears in Collections:Journal/Magazine Article
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