Journal ArticleDOI
Towards Improving the Lexicon-Based Approach for Arabic Sentiment Analysis
Nawaf A. Abdulla,Nizar A. Ahmed,Mohammed A. Shehab,Mahmoud Al-Ayyoub,Mohammed N. Al-Kabi,Saleh Y. Al-Rifai +5 more
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TLDR
The discussions in this paper take the reader through the detailed steps of building the main two components of the lexicon-based SA approach: the Lexicon and the SA tool.Abstract:
The emergence of the Web 2.0 technology generated a massive amount of raw data by enabling Internet users to post their opinions on the web. Processing this raw data to extract useful information can be a very challenging task. An example of important information that can be automatically extracted from the users' posts is their opinions on different issues. This problem of Sentiment Analysis SA has been studied well on the English language and two main approaches have been devised: corpus-based and lexicon-based. This work focuses on the later approach due to its various challenges and high potential. The discussions in this paper take the reader through the detailed steps of building the main two components of the lexicon-based SA approach: the lexicon and the SA tool. The experiments show that significant efforts are still needed to reach a satisfactory level of accuracy for the lexicon-based Arabic SA. Nonetheless, they do provide an interesting guide for the researchers in their on-going efforts to improve lexicon-based SA.read more
Citations
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Journal ArticleDOI
Approaches, Tools and Applications for Sentiment Analysis Implementation
TL;DR: The paper gives an overview of the different sentiment classification approaches and tools used for sentiment analysis and provides a classification of approaches with respect to features/techniques and advantages/limitations.
Journal ArticleDOI
A comprehensive survey of arabic sentiment analysis
TL;DR: This survey presents a comprehensive overview of the works done so far on Arabic SA and tries to identify the gaps in the current literature laying foundation for future studies in this field.
Journal ArticleDOI
A review of sentiment analysis research in Arabic language
TL;DR: This article conducted an in-depth qualitative study of the most important research works in this context by discussing strengths and limitations of existing approaches and survey both approaches that leverage machine translation or transfer learning to adapt English resources to Arabic and approaches that stem directly from the Arabic language.
Journal ArticleDOI
A Survey of Opinion Mining in Arabic: A Comprehensive System Perspective Covering Challenges and Advances in Tools, Resources, Models, Applications, and Visualizations
Gilbert Badaro,Ramy Baly,Hazem Hajj,Wassim El-Hajj,Khaled Bashir Shaban,Nizar Habash,Ahmad Al-Sallab,Ali Hamdi +7 more
TL;DR: This article provides a comprehensive system perspective by covering advances in different aspects of an opinion-mining system, including advances in NLP software tools, lexical sentiment and corpora resources, classification models, and applications of opinion mining.
Journal ArticleDOI
A Proposed Lexicon-Based Sentiment Analysis Approach for the Vernacular Algerian Arabic
TL;DR: A new lexicon-based sentiment analysis approach to address the specific aspects of the vernacular Algerian Arabic fully utilized in social networks is proposed.
References
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Book
Opinion Mining and Sentiment Analysis
Bo Pang,Lillian Lee +1 more
TL;DR: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems and focuses on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis.
Posted Content
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
TL;DR: A simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (Thumbs down) if the average semantic orientation of its phrases is positive.
Proceedings Article
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
TL;DR: This article proposed an unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended(thumbs down) based on the average semantic orientation of phrases in the review that contain adjectives or adverbs.
Book
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Dan Jurafsky,James Martin +1 more
TL;DR: This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora, to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation.
Journal ArticleDOI
Lexicon-based methods for sentiment analysis
TL;DR: The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation, and is applied to the polarity classification task.