Sentiment classification on arabic corpora. A preliminary cross-study

@article{Mountassir2013SentimentCO,
  title={Sentiment classification on arabic corpora. A preliminary cross-study},
  author={Asmaa Mountassir and Houda Benbrahim and Ilham Berrada},
  journal={Document Num{\'e}rique},
  year={2013},
  volume={16},
  pages={73-96}
}
The rise of social media (such as online web forums and social networking sites) has attracted interests to mining and analyzing opinions available on the web. The online opinion has become the object of studies in many research areas; especially that called “Opinion Mining and Sentiment Analysis”. Several interesting and advanced works were performed on few languages (in particular English). However, there were very few studies on Morphologically Rich Languages such as Arabic. This paper… Expand
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References

SHOWING 1-10 OF 49 REFERENCES
Bilingual Experiments with an Arabic-English Corpus for Opinion Mining
TLDR
This work presents an Opinion Corpus for Arabic (OCA) composed of Arabic reviews extracted from specialized web pages related to movies and films using this language, and translates the OCA corpus into English, generating the EVOCA corpus (English Version of OCA). Expand
An empirical study to address the problem of Unbalanced Data Sets in sentiment classification
TLDR
The study carried out to address the problem of unbalanced data sets in supervised sentiment classification in a multi-lingual context proposes three different methods to under-sample the majority class documents and shows that the four under-sampling methods are typically competitive. Expand
Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
TLDR
Stylistic features significantly enhanced performance across all testbeds while EWGA also outperformed other feature selection methods, indicating the utility of these features and techniques for document-level classification of sentiments. Expand
An empirical study of sentiment analysis for chinese documents
TLDR
The experimental results indicate that IG performs the best for sentimental terms selection and SVM exhibits the best performance for sentiment classification, and it is found that sentiment classifiers are severely dependent on domains or topics. Expand
Sentiment classification of online reviews to travel destinations by supervised machine learning approaches
TLDR
This research compared three supervised machine learning algorithms of Naive Bayes, SVM and the character based N-gram model for sentiment classification of the reviews on travel blogs for seven popular travel destinations in the US and Europe. Expand
Feature reduction techniques for Arabic text categorization
TLDR
This paper presents and compares three feature reduction techniques that were applied to Arabic text, which include stemming, light stemming, and word clusters, to reduce the size of document vectors without affecting the accuracy of the classifiers. Expand
Dependency Tree-based Sentiment Classification using CRFs with Hidden Variables
TLDR
Experimental results of sentiment classification of Japanese and English subjective sentences using conditional random fields with hidden variables showed that the method performs better than other methods based on bag-of-features. Expand
Stemming Versus Light Stemming as Feature Selection Techniques for Arabic Text Categorization
This paper compares and contrasts two feature selection techniques when applied to Arabic corpus; in particular; stemming, and light stemming were employed. With stemming, words are reduced to theirExpand
Subjectivity and Sentiment Analysis of Modern Standard Arabic
TLDR
This study presents a newly developed manually annotated corpus of Modern Standard Arabic together with a new polarity lexicon and shows that by explicitly accounting for the rich morphology the system is able to achieve significantly higher levels of performance. Expand
Using appraisal groups for sentiment analysis
TLDR
A new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good'' or ``not terribly funny'' is presented, based on several task-independent semantic taxonomies based on Appraisal Theory. Expand
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