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| 024 |
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|3 10.21608/JSSA.2019.38725
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| 041 |
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|a eng
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| 044 |
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|b مصر
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| 100 |
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|9 521057
|a Omar, Abdulfattah
|e Author
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| 245 |
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|a Cybercrime and Authorship Detection in Very Short Texts:
|b A Quantitative Morpho-Lexical Approach
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| 260 |
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|b جامعة عين شمس - كلية البنات للآداب والعلوم والتربية
|c 2019
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| 300 |
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|a 291 - 316
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| 336 |
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|a بحوث ومقالات
|b Article
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| 520 |
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|b The present study proposes an integrated framework that considers letter- pair frequencies / combinations along with the lexical features of documents. Drawing on a quantitative morpho-lexical approach, the study tests the hypothesis that letter information or mapping carries unique stylistic features; and therefore detecting stable word combinations and morphological patterns can be used to enhance the authorship performance in relation to very short texts. The data used for analysis is a corpus of 12240 tweets derived from 87 Twitter accounts. Self-organizing maps (SOMs) model is used for classifying the input patterns that share common features together as a clue that tweets grouped under one class membership are written by the same author. Results indicate that the classification accuracy based on the proposed system is around 76%. Up to 22% of this accuracy was lost, however, when only distinctive words were used, and 26% was lost when the classification performance was based on letter combinations and morphological patterns only. The integration of letter-pairs and morphological patterns had the advantage of improving the accuracy of determining the author of a given tweet. This indicates that the integration of different linguistic variables into an integrated system leads to a better classification performance of very short texts. It is also clear that the use of the self-organizing map (SOM) led to better clustering performance for its capacity to integrate two different linguistic levels of each author profile together.
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| 653 |
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|a الجرائم الإلكترونية
|a حقوق الملكية
|a اللسانيات الحاسوبية
|a خرائط التنظيم الذاتي
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| 692 |
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|b Authorship Detection
|b Forensic Linguistics
|b Morphological Patterns
|b Lexical Features
|b Letter Pair Frequencies
|b Self Organizing Maps (Soms)
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| 773 |
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|4 الادب
|6 Literature
|c 010
|e Academic Research Journal for Arts
|f Mağallaẗ Al-Baḥṯ Al-ʿilmī Fī Al-Ādāb
|l 001
|m ع20, ج1
|o 0795
|s مجلة البحث العلمي في الآداب
|v 020
|x 2356-8321
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| 856 |
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|u 0795-020-001-010.pdf
|n https://jssa.journals.ekb.eg/article_38725.html
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| 930 |
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|d y
|p y
|q y
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| 995 |
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|a AraBase
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| 999 |
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|c 978060
|d 978060
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