Stylometric model for detecting oath expressions: A case study for Quranic texts.
The Quranic oath is God's emphasizing the importance or truthfulness of a concept. Oaths are multifaceted, rich expressions, in which a single oath contains a line of meaning and a variety of aspects. This study proposes a new stylometric model for detecting apparent and narrative oaths. Toward this...
| Published in: | Digital Scholarship in the Humanities Vol. 31; no. 1; pp. 1 - 21 |
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| Main Authors: | , , , |
| Format: | Article |
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Oxford University Press / USA
4/1/2016
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=114160243&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 114160243 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: 4/1/2016 vid: 31 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 114160243 10.1093/llc/fqu038 ppf: 1 ppct: 20 formats: fmt: @attributes: type: P size: 5.3MB tig: atl: Stylometric model for detecting oath expressions: A case study for Quranic texts. aug: au: Alqurneh, Ahmad Mustapha, Aida Azmi Murad, Masrah Azrifah Sharef, Nurfadhlina Mohd affil: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, Malaysia su: Stylometry Oaths in the Qur'an Qur'an Islamic sacred books Word frequency sug: subj: Stylometry Oaths in the Qur'an Qur'an Islamic sacred books Word frequency ab: The Quranic oath is God's emphasizing the importance or truthfulness of a concept. Oaths are multifaceted, rich expressions, in which a single oath contains a line of meaning and a variety of aspects. This study proposes a new stylometric model for detecting apparent and narrative oaths. Toward this end, two types of application-specific features from a stylometric perspective--structural and content- specific features--were examined. The stylometric features were extracted, and a Bayesian network was constructed to model such features. The stylometric model of oaths was then evaluated through a series of machine-learning experiments using various classifiers: the Bayesian network, a decision tree, instancebased learning, and a neural network. These classification experiments focused on applying stylometric features in apparent and narrative oaths. The experiments covered two datasets: the entire Quran and the smaller dataset of Juz' 'Amma. The results led to two main conclusions. First, stylometric application-specific features are best used in their entirety--both structural-based and content-specific--rather than as two separate entities. Second, applying stylometric features was more significant in Juz' 'Amma, in which 40% of its surahs (chapters) contain oath statements. Finally, the stylometric model was extended for oath styles detection using three additional stylometric features--syntactic, character, and lexical, and it was analyzed using statistical approach. 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: 2016 holdings: @attributes: islocal: N |
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