Semantic Sentiment Analysis of Arabic Texts
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 2
Abstract
Twitter considered as a rich resource to collect people's opinions in different domains and attracted researchers to develop an automatic Sentiment Analysis (SA) model for tweets. In this work, a semantic Arabic Twitter Sentiment Analysis (ATSA) model is developed based on supervised machine learning (ML) approaches and semantic analysis. Most of the existing Arabic SA approaches represent tweets based on the bag-of-words (BoW) model. The main limitation of this model is that it is semantically weak; where words considered as independent features and ignore the semantic associations between them. As a result, synonymous words that appear in two tweets are represented as different independent features. To overcome this limitation, this work proposes enriching the tweets representation with concepts utilizing Arabic WordNet (AWN) as an external knowledge base. In addition, different concepts representation approaches are developed and evaluated with naïve Bayes (NB) and support vector machine (SVM) ML classifiers on an Arabic Twitter dataset. The experimental results indicate that using concepts features improves the performance of the ATSA model compared with the basic BoW representation. The improvement reached 4.48% with the SVM classifier and 5.78% with the NB classifier.
Authors and Affiliations
Sana Alowaidi, Mustafa Saleh, Osama Abulnaja
Keywords
Related Articles
- EP ID EP249154
- DOI 10.14569/IJACSA.2017.080234
- Views 110
- Downloads 0
Wiki-Based Stochastic Programming and Statistical Modeling System for the Cloud
Scientific software is a special type of software because its quality has a huge impact on the quality of scientific conclusions and scientific progress. However, it is hard to ensure required quality of the software bec...
Cross-Lingual Sentiment Classification from English to Arabic using Machine Translation
Cross-lingual sentiment learning is becoming increasingly important due to the multilingual nature of user-generated content on social media and the scarce resources for languages other than English. However, cross-lingu...
Analysis of Significant Factors for Dengue Infection Prognosis Using the Random Forest Classifier
Random forests have emerged as a versatile and highly accurate classification and regression methodology, requiring little tuning and providing interpretable outputs. Here, we briefly explore the possibility of applying...
FINGERPRINT IMAGE SEGMENTATION USING HAAR WAVELET AND SELF ORGANIZING MAP
Fingerprint image segmentation is one of the important preprocessing steps in Automatic Fingerprint Identification Systems (AFIS). Segmentation separates image background from image foreground, removing unnecessary infor...
Analysis and Formal Model of RFID-Based Patient Registration System
Patient Registration System (PRS) is an important part of hospital environment. Therefore, semiformal model of Patient Registration System that registers the patients by assigning Radio Frequency Identification (RFID) ca...