Polarity classification of social media feeds using incremental learning - A Deep Learning Approach

Author(s):  
Suresh JAGANATHAN ◽  
Sathya MADHUSUDHANAN
Author(s):  
Mohammed N. Al-Kabi ◽  
Heider A. Wahsheh ◽  
Izzat M. Alsmadi

Sentiment Analysis/Opinion Mining is associated with social media and usually aims to automatically identify the polarities of different points of views of the users of the social media about different aspects of life. The polarity of a sentiment reflects the point view of its author about a certain issue. This study aims to present a new method to identify the polarity of Arabic reviews and comments whether they are written in Modern Standard Arabic (MSA), or one of the Arabic Dialects, and/or include Emoticons. The proposed method is called Detection of Arabic Sentiment Analysis Polarity (DASAP). A modest dataset of Arabic comments, posts, and reviews is collected from Online social network websites (i.e. Facebook, Blogs, YouTube, and Twitter). This dataset is used to evaluate the effectiveness of the proposed method (DASAP). Receiver Operating Characteristic (ROC) prediction quality measurements are used to evaluate the effectiveness of DASAP based on the collected dataset.


2021 ◽  
Vol 128 ◽  
pp. 103785
Author(s):  
Yongqing Jiang ◽  
Dandan Pang ◽  
Chengdong Li

Author(s):  
Donghyuk Shin ◽  
Shu He ◽  
Gene Moo Lee ◽  
Andrew B. Whinston ◽  
Suleyman Cetintas ◽  
...  

Author(s):  
Alessio P. Buccino ◽  
Torbjorn V. Ness ◽  
Gaute T. Einevoll ◽  
Gert Cauwenberghs ◽  
Philipp D. Hafliger

Author(s):  
Joni Salminen ◽  
Rohan Gurunandan Rao ◽  
Soon-gyo Jung ◽  
Shammur A. Chowdhury ◽  
Bernard J. Jansen

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