Data Mining and Privacy of Social Network Sites' Users: Implications of the Data Mining Problem.
This paper explores the potential of data mining as a technique that could be used by malicious data miners to threaten the privacy of social network sites (SNS) users. It applies a data mining algorithm to a real dataset to provide empirically-based evidence of the ease with which characteristics a...
| Publicado en: | Science & Engineering Ethics Vol. 21; no. 4; pp. 941 - 967 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Aug2015
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=103737057&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 103737057 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 13533452 GNI jtl: Science & Engineering Ethics issn: 13533452 maglogo: N pubinfo: dt: Aug2015 vid: 21 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 103737057 10.1007/s11948-014-9564-6 ppf: 941 ppct: 26 formats: fmt: @attributes: type: P size: 667KB tig: atl: Data Mining and Privacy of Social Network Sites' Users: Implications of the Data Mining Problem. aug: au: Al-Saggaf, Yeslam Islam, Md affil: School of Computing and Mathematics, Charles Sturt University, Boorooma Street Wagga Wagga 2678 Australia Centre for Research in Complex Systems, School of Computing and Mathematics, Charles Sturt University, Bathurst Australia su: Data mining Online social networks research Computer security ethics Content analysis Decision trees Ethics Mathematical models sug: subj: Data mining Online social networks research Computer security ethics Content analysis Decision trees Ethics Mathematical models keyword: Logic rules Privacy Social network sites (SNS) ab: This paper explores the potential of data mining as a technique that could be used by malicious data miners to threaten the privacy of social network sites (SNS) users. It applies a data mining algorithm to a real dataset to provide empirically-based evidence of the ease with which characteristics about the SNS users can be discovered and used in a way that could invade their privacy. One major contribution of this article is the use of the decision forest data mining algorithm (SysFor) to the context of SNS, which does not only build a decision tree but rather a forest allowing the exploration of more logic rules from a dataset. One logic rule that SysFor built in this study, for example, revealed that anyone having a profile picture showing just the face or a picture showing a family is less likely to be lonely. Another contribution of this article is the discussion of the implications of the data mining problem for governments, businesses, developers and the SNS users themselves. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Science & Engineering Ethics is a copyright of Springer, 2015. All Rights Reserved. item: Science & Engineering Ethics holder: Springer Nature dt: @attributes: year: 2015 holdings: @attributes: islocal: N |
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