The Effectiveness of Stemming in the Stylometric Authorship Attribution in Arabic

Omar, Abdulfattah; Hamouda, Wafya Ibrahim

doi:10.14569/ijacsa.2020.0110114

Cited by 17 publications

(15 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2020). They also support the arguments that the Arabic morphological system carries distinctive stylistic features that can be usefully used in authorship recognition applications (Alghamdi & Selamat, 2019;Omar, Elghayesh, & Kassem, 2019;Omar & Hamouda, 2020) Conclusion So far, authorship recognition of social media texts in Arabic poses different challenges for researchers, professionals, and program developers. This can be attributed to various reasons, including the linguistic specific rules that make Arabic different from other Western languages and the peculiar nature of the social media language.…”

Section: Resultssupporting

confidence: 67%

Towards a Stylometric Authorship Recognition Model for the Social Media Texts in Arabic

Alsager¹

2020

AWEJ

View full text Add to dashboard Cite

Numerous studies have been concerned with developing new authorship recognition systems to address the increasing rates of cybercrimes associated with the anonymous nature of social media platforms, which still offer the opportunity for the users not to reveal their true identities. Nevertheless, it is still challenging to identify the real authors of social media’s offensive and inappropriate content. These contents are usually very short; therefore, it is challenging for stylometric authorship systems to assign controversial texts to their real authors based on the salient and distinctive linguistic features and patterns within these contents. This research introduces a new stylometric authorship system that considers both the shortness of data and the peculiar linguistic properties of Arabic. A corpus of 20, 357 tweets from 134 Twitter users. A document clustering based on Document Index Graph (DIG) model was used to classify input patterns in the tweets that shared common linguistic features. A comparative analysis using Vector Space Clustering (VSC) model based on the Bag of Words (BOW) model, conventionally used in authorship recognition applications, was used. Results indicate that the proposed system is more accurate than other standard authorship systems mainly based on vector space clustering methods. It was also clear that the model had the advantage of providing complete information about the documents and the degree of overlap between every pair of documents, which was useful in determining the similarity between documents.

show abstract

Section: Resultssupporting

confidence: 67%

Towards a Stylometric Authorship Recognition Model for the Social Media Texts in Arabic

Alsager¹

2020

AWEJ

View full text Add to dashboard Cite

show abstract

“…Given the fact that not all languages are identical, localization developers, therefore, need to address the linguistic challenges and peculiarities of Arabic, including its morphology, writing system, and dialectal diversity. Indeed, the peculiar linguistic features of Arabic remain among the most serious challenges that have negative impacts on the NPL applications including information retrieval, machine translation, and definitely localization [52][53][54][55][56].…”

Section: Analysis and Discussionmentioning

confidence: 99%

An Evaluation of the Localization Quality of the Arabic Versions of Learning Management Systems

Omar¹

2021

IJACSA

Self Cite

View full text Add to dashboard Cite

The recent years have witnessed the development of numerous Learning Management Systems (LMSs) to address the increasing needs of individuals and institutions all over the world. For accessibility and commercial purposes, many of these LMSs are released in different languages using what is known as localization systems. In this regard, there has been a parallel between the development of LMSs on one hand and the localization systems on the other. One main aspect in the recent evaluation systems and studies of LMSs is localization quality. Despite the prolific literature on localization quality, very little has been done on Arabic localization. As thus, this study is concerned with the evaluation of the localization quality of the Arabic version of LMSs. In order to explore users' perceptions towards the Arabic versions of the LMSs, an online questionnaire was conducted. Participants were asked about their familiarity with LMSs and whether they used the Arabic versions of these systems. They were also asked about their experiences with the Arabic localization of these systems and whether they faced any problems in dealing with the Arabic version. The findings indicate that translation inconsistencies are the main problems with the Arabic versions of different LMSs including Blackboard Learn, Microsoft Teams, and Zoom. These problems have negative impacts on the effectiveness and reliability of these systems in schools, universities, and training institutions. For the proper implementation of LMSs both localization and translation should go hand-in-hand. Localization developers and LMSs designers need to consider the linguistic the peculiar linguistic features of Arabic. The findings of the study have implications to translation programs in Arab universities and training institutions. Program designers should integrate translation technologies and localization systems into translation studies. They need to consider the changes within the translation industry. The study was limited to the study of translation quality in the Arabic versions of the localized LMSs. The localization quality of other software programs, games, websites, and applications needs to be explored. Finally, it is recommended to develop a quality matrix that encompasses all the dimensions and peculiarities of Arabic localization.

show abstract

“…It can be concluded that the letter mapping and morphological patterns of each author can thus serve as distinctive linguistic stylometric features that can be usefully used for determining the authors of disputed texts in Arabic. It should be noted that letter mapping and morphological patterns have long been disregarded in authorship applications in Arabic which were traditionally based on stemming procedures as a pre-processing procedure in NLP applications of Arabic (Omar, Hamouda, 2020). In this regard, the distinctive morphological features of Arabic morphology should be considered in NLP applications including authorship attribution.…”

Section: Discussionmentioning

confidence: 99%

“…Numerous studies have attempted to explain the stylistic and linguistic properties of authors through quantitative methods, which have become more sophisticated with the availability of computationalrather than non-computationalmethods (El Bakly, Darwish & Hefny; Omar, Elghayesh & Kassem, 2019). Many studies agree that the development of computational methods has enhanced the efficiency and accuracy of stylometric studies, since computer systems have capacities for analyzing large quantities of data (Ison, 2020;Omar & Hamouda, 2020;Zhao, Li, Qi & Da Xu, 2020). Thus, "[C]omputational stylistics provides a valuable methodology in helping to answer the question, 'Who wrote it?'"…”

Section: Literature Reviewmentioning

confidence: 99%

“…These are standard preprocessing procedures in document clustering applications. Although stemming is one such procedure, it was not executed in this study as the unique stylistic features of affixation in Arabic make it possible to enhance detection and attribution of authorship using morphological information Omar & Hamouda, 2020).…”

Section: Data Collection and Preparationmentioning

confidence: 99%

See 1 more Smart Citation

Authorship attribution of Morsi Gameel Aziz’s lyrics: A clustering-based stylometry approach

Omar

2021

JLLS

Self Cite

View full text Add to dashboard Cite

Numerous studies have addressed the issue of the authorship of Morsi Gameel Aziz's lyrics. These studies have traditionally been based on chronological criteria for determining the real authors of disputed lyrics. To date, there is no agreement on the real authors of these disputed lyrics. This can mainly be attributed to both selectivity and the lack of empirical evidence in such studies, raising questions about the reliability of such approaches. With the advent of machine learning systems and data mining techniques, it is now possible to process thousands of texts using replicable methods. Thus, this study seeks to address the issue of the authorship of Morsi Gameel Aziz's lyrics making use of these advances by applying a clustering-based stylometry approach. The hypothesis is that lyrics grouped or clustered together are more likely to be written by the same poet. A corpus of 1,089 lyrics was built, including all known lyrics attributed to Aziz and the lyrics of the poets thought to be the real authors of the disputed lyrics. The lyrics were clustered using the Gibbs sampling Dirichlet multinomial mixture (GSDMM) technique and were assigned to four main classes, with the 12 disputed lyrics clustered within Aziz's class. Based on this, it is clear that the GSDMM model is effective and reliable in clustering short documents in Arabic. The results of the study show that machine learning systems and stylometric authorship techniques can be used in resolving many authorship questions that remain controversial and unanswered in Arabic literature.

show abstract

The Effectiveness of Stemming in the Stylometric Authorship Attribution in Arabic

Cited by 17 publications

References 24 publications

Towards a Stylometric Authorship Recognition Model for the Social Media Texts in Arabic

Towards a Stylometric Authorship Recognition Model for the Social Media Texts in Arabic

An Evaluation of the Localization Quality of the Arabic Versions of Learning Management Systems

Authorship attribution of Morsi Gameel Aziz’s lyrics: A clustering-based stylometry approach

Contact Info

Product

Resources

About