Framework for Sentiment Analysis of Arabic Text

被引：9

作者：

Almuqren, Latifah ^{[1
]}

Cristea, Alexandra I. ^{[1
]}

机构：

[1] Univ Warwick, Dept Comp Sci, Coventry, W Midlands, England

来源：

PROCEEDINGS OF THE 27TH ACM CONFERENCE ON HYPERTEXT AND SOCIAL MEDIA (HT'16) | 2016年

关键词：

Semantic Sentiment Analysis (SSA); Arabic; Twitter; Sentiment; CUSTOMER SATISFACTION;

D O I：

10.1145/2914586.2914610

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper analyses challenges, and provides a model and a framework for mining Arabic tweets to measure customer satisfaction toward telecom companies in Saudi Arabia, to predict the ratio of customer churn and overcome the specific challenges with the semantic sentiment analysis of Arabic text.

引用

页码：315 / 317

页数：3

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