AraSenTi-Lexicon: A Different Approach

被引：4

作者：

AlNegheimish, Hadeel ^{[1
]}

Alshobaili, Jowharah ^{[2
]}

AlMansour, Nora ^{[1
]}

Bin Shiha, Rawan ^{[1
]}

AlTwairesh, Nora ^{[1
]}

Alhumoud, Sarah ^{[3
]}

机构：

[1] King Saud Univ, Coll Comp & Informat Sci, Riyadh, Saudi Arabia

[2] Qassim Univ, Coll Comp, Buraydah, Saudi Arabia

[3] Al Imam Muhammad Ibn Saud Islamic Univ, Dept Comp Sci, Riyadh, Saudi Arabia

来源：

SOCIAL COMPUTING AND SOCIAL MEDIA: APPLICATIONS AND ANALYTICS, SCSM 2017, PT II | 2017年 / 10283卷

关键词：

Sentiment analysis; Arabic sentiment lexicon; Lexicon generation; Dialectal arabic; Twitter;

D O I：

10.1007/978-3-319-58562-8_18

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

With the spread of social media, the demand for automated systems that analyze these massive amounts of data on the Web is increasing. One domain for these systems is sentiment analysis(SA). SA is designed to extract sentiment from text; this is often accomplished by using lexicons that indicate the sentiment polarity of words. While there are many English lexicons that are available, there is a lack of Arabic lexicons. In previous work, an attempt was made to generate an Arabic sentiment lexicon extracted from Twitter using the Pointwise Mutual Information (PMI) statistical method. In this paper, we extend the work by using two different statistical approaches: Chi-Square and Entropy to generate the lexicons. Intrinsic and extrinsic evaluation was conducted to compare the three lexicons. The results showed the superiority of PMI.

引用

页码：226 / 235

页数：10

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