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Title |
Application of Topic Modeling Techniques in Arabic Content: A Systematic Review |
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Author |
Maram Alhmiyani and Huda Alhazmi |
| Citation |
Vol. 23 No. 6 pp. 1-12 |
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Abstract |
With the rapid increase of user generated data on digital platforms, the task of categorizing and classifying theses huge data has become difficult. Topic modeling is an unsupervised machine learning technique that can be used to get a summary from a large collection of documents. Topic modeling has been widely used in English content, yet the application of topic modeling in Arabic language is limited. Therefore, the aim of this paper is to provide a systematic review of the application of topic modeling algorithms in Arabic content. Using a well-known and trusted databases including ScienceDirect, IEEE Xplore, Springer Link, and Google Scholar. Considering the publication date from 2012 to 2022, we got 60 papers. After refining the papers based on predefined criteria, we resulted in 32 papers. Our result show that unfortunately the application of topic modeling techniques in Arabic content is limited. |
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Keywords |
Arabic content, Topic modeling, digital platform, LDA, topic classification. |
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