Author identification with feature transformation method.
Over the last few decades, there has been tremendous growth in online communication through different types of media. Communication via the Internet is anonymous, which causes a critical issue regarding identity tracing. Authorship identification can apply to tasks such as identifying an anonymous a...
| Publicado en: | Digital Scholarship in the Humanities Vol. 35; no. 3; pp. 642 - 652 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Oxford University Press / USA
Sep2020
|
| 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=146172317&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 146172317 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Sep2020 vid: 35 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 146172317 10.1093/llc/fqz052 ppf: 642 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P size: 230KB tig: atl: Author identification with feature transformation method. aug: au: Tamboli, Mubin Shoukat Prasad, Rajesh affil: Department of Computer Engineering , Matoshri College of Engineering, Nashik, Maharashtra, India Sinhgad Institute of Technology and Science , Narhe, Pune, India su: Anonymous authors Identification Algorithms Time measurements Authors sug: subj: Anonymous authors Identification Algorithms Time measurements Authors ab: Over the last few decades, there has been tremendous growth in online communication through different types of media. Communication via the Internet is anonymous, which causes a critical issue regarding identity tracing. Authorship identification can apply to tasks such as identifying an anonymous author, detecting plagiarism, or finding a ghostwriter. Previous research has outlined the various methods and their improvements for the identification of anonymous authors based on stylometry. However, changes in the writing style of an author over a long period has not been addressed. In this article, we propose a methodology for author identification where the writing style of an author changes. The proposed methodology consists of two phases: the first will show the change in writing style of the author and in another phase the change is mitigated by a new feature normalization technique. A novel Transform Feature to Current Time function is proposed for normalization, where features are shifted to current time and made available for further classification. A machine-learning algorithm is used to identify an author candidate. The experiments of the proposed methodology conducted on a set of text samples by several authors were collected over a different time period and the results show an improvement in performance. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
|---|