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.
Highlights
Due to the emergence of Web2.0, users can share their opinions and sentiments on a variety of topics in new interactive forms where users are passive information receivers
Deep learning approaches have captured the attention of researchers because it has significantly outperformed traditional methods
The following figure (Fig. 1) Summarize the accuracy of works using movie review data set [31]. This From the figure (Fig. 1), we find that work [6], which used a hybrid method of classification based on the coupling of NB and genetic algorithm (GA), gave the best results in terms of accuracy
Summary
Due to the emergence of Web2.0, users can share their opinions and sentiments on a variety of topics in new interactive forms where users are passive information receivers. Sentence level analysis The task at this level is to determine if each sentence has expressed an opinion This level distinguishes the objective sentences expressing factual information and subjective sentences expressing opinions. In this case, treatments are twofold; firstly identify if the sentence has expressed or not an opinion, assess the polarity of opinion. The main difficulty comes from the fact that objective sentences can be carrying opinion This level performs a finer analysis and requires the use of natural language processing. In this level, opinion is characterized by a polarity and a target of opinion. Last section concludes our study and discusses some future directions for research
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