EAI Endorsed Transactions on Context-aware Systems and Applications 18(13): e2

Research Article

Document Level Sentiment Analysis: A survey

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  • @ARTICLE{10.4108/eai.14-3-2018.154339,
        author={S. Behdenna and F. Barigou and G. Belalem},
        title={Document Level Sentiment Analysis: A survey},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={18},
        number={13},
        publisher={EAI},
        journal_a={CASA},
        year={2018},
        month={3},
        keywords={opinion mining, sentiment analysis, opinion, review, document, machine learning.},
        doi={10.4108/eai.14-3-2018.154339}
    }
    
  • S. Behdenna
    F. Barigou
    G. Belalem
    Year: 2018
    Document Level Sentiment Analysis: A survey
    CASA
    EAI
    DOI: 10.4108/eai.14-3-2018.154339
S. Behdenna1,*, F. Barigou1, G. Belalem1
  • 1: Department of Computer Science, Faculty of Sciences, University of Oran 1 Ahmed Ben Bella, PB 1524 El M’Naouer, Oran, Algeria (31000)
*Contact email: selma_salima@yahoo.fr

Abstract

Sentiment analysis becomes a very active research area in the text mining field. It aims to extract people's opinions, sentiments, and subjectivity from the texts. Sentiment analysis can be performed at three levels: at document level, at sentence level and at aspect level. An important part of research effort focuses on document level sentiment classification, including works on opinion classification of reviews. This survey paper tackles a comprehensive overview of the last update of sentiment analysis at document level. The main target of this survey is to give nearly full image of sentiment analysis application, challenges and techniques at this level. In addition, some future research issues are also presented.