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Haidi Badr, Nayer Wanas and Magda Fayek
Unsupervised domain adaptation (UDA) presents a significant challenge in sentiment analysis, especially when faced with differences between source and target domains. This study introduces Weighted Sequential Unsupervised Domain Adaptation (WS-UDA), a no...
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Ashokkumar Palanivinayagam, Claude Ziad El-Bayeh and Robertas Dama?evicius
Machine-learning-based text classification is one of the leading research areas and has a wide range of applications, which include spam detection, hate speech identification, reviews, rating summarization, sentiment analysis, and topic modelling. Widely...
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Ala? M. Al-Zoubi, Antonio M. Mora and Hossam Faris
During the recent COVID-19 pandemic, people were forced to stay at home to protect their own and others? lives. As a result, remote technology is being considered more in all aspects of life. One important example of this is online reviews, where the num...
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Zhi-Yuan Zeng, Jyun-Jie Lin, Mu-Sheng Chen, Meng-Hui Chen, Yan-Qi Lan and Jun-Lin Liu
Consumers? purchase behavior increasingly relies on online reviews. Accordingly, there are more and more deceptive reviews which are harmful to customers. Existing methods to detect spam reviews mainly take the problem as a general text classification ta...
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Naveed Hussain, Hamid Turab Mirza, Ghulam Rasool, Ibrar Hussain and Mohammad Kaleem
Online reviews about the purchase of products or services provided have become the main source of users? opinions. In order to gain profit or fame, usually spam reviews are written to promote or demote a few target products or services. This practice is ...
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Wen Zhang, Chaoqi Bu, Taketoshi Yoshida and Siguang Zhang
Spam reviews are increasingly appearing on the Internet to promote sales or defame competitors by misleading consumers with deceptive opinions. This paper proposes a co-training approach called CoSpa (Co-training for Spam review identification) to identi...
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