Central Kurdish Sentiment Analysis Using Deep Learning
نویسندگان
چکیده
Sentiment Analysis (SA) as a type of opinion mining and more general topic than polarity detection, is widely used for analyzing user's reviews or comments online expressions, which implemented using various techniques among the Artificial Neural Network (ANN) most popular one. This paper addresses development an SA system Central Kurdish language (CKB) deep learning. Increasing efficiency strengthening relies on robust model. In addition, creating training model, collecting large amount text corpus required we have created size 300 million tokens CKB. Also, to train collected 14,881 Facebook, then they are labeled manually. The combination Word2Vec model Long Short-Term Memory (LSTM) classifier create CKB dataset. These learning-based well-known methods in this field received high performance languages. proposed method 3 classes %71.35 accuracy. result superior best-reported
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ژورنال
عنوان ژورنال: Ma?alla? ??mi?a? al-anb?r li-l-?ul?m al-?irfa?
سال: 2022
ISSN: ['1991-8941', '2706-6703']
DOI: https://doi.org/10.37652/juaps.2022.176501