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Text mining based sentiment analysis using a novel deep learning approach | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 595-604 اصل مقاله (3.3 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5378 | ||
| نویسندگان | ||
| Enas Fadhil Abdullah1؛ Suad A. Alasadi* 2؛ Alyaa Abdulhussein Al-Joda3 | ||
| 1Faculty of Education for Girls, University of Kufa, Al- Najaf, Iraq | ||
| 2College of Information Technology, University of Babylon, Babil, Iraq | ||
| 3Engineering Technical College of Al-Najaf,Al-Furat Al-Awsat Technical University (ATU), Al-Najaf, Iraq | ||
| تاریخ دریافت: 27 اسفند 1399، تاریخ بازنگری: 19 اردیبهشت 1400، تاریخ پذیرش: 02 تیر 1400 | ||
| چکیده | ||
| Leveraging text mining for sentiment analysis, and integrating text mining and deep learning are the main purposes of this paper. The presented study includes three main steps. At the first step, pre-processing such as tokenization, text cleaning, stop word, stemming, and text normalization has been utilized. Secondly, feature from review and tweets using Bag of Words (BOW) method and Term Frequency $\_$Inverse Document Frequency is extracted. Finally, deep learning by dense neural networks is used for classification. This research throws light on understanding the basic concepts of sentiment analysis and then showcases a model which performs deep learning for classification for a movie review and airline$\_$ sentiment data set. The performance measure in terms of precision, recall, F1-measure and accuracy were calculated. Based on the results, the proposed method achieved an accuracy of $95.38\%$ and $93.84\%$ for a movie review and Airline$\_$ sentiment, respectively. | ||
| کلیدواژه‌ها | ||
| Sentiment analysis؛ Deep learning؛ DNN؛ Text mining | ||
| مراجع | ||
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