Sensitivity of Arabic Sentiment Analysis Tools

被引:1
|
作者
Conlon, Brian [1 ]
Brenner, Paul [1 ]
机构
[1] Univ Notre Dame, Notre Dame, IN 46556 USA
关键词
social networks; natural language processing; sentiment analysis; WEIGHTED KAPPA;
D O I
10.1109/SNAMS52053.2020.9336535
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
While the accuracy of Arabic text sentiment analysis tools continues to improve, the accuracy continues to lag behind similar tools for Latin-based languages. In this work we review some of the unique challenges inherent in the Arabic language that contribute to this accuracy lag beyond the scale-based economic drivers propelling enhanced accuracy in other languages. We then identify some of the most promising new tools and provide a framework for evaluating the differences in sensitivity and polarity. While there is not yet a universal standard scale for sentiment polarity, we attempt to provide a normalized basis upon which to compare the degree to which various tools tend to classify text segments toward either end (or the middle) of the polarity spectrum.
引用
收藏
页码:195 / 200
页数:6
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