Utilization of deep learning and semantic analysis for opinion mining in information extraction: a review

Mekala Susmitha, Shaik Razia


In concern of the increasing availability and popularity of the opinion information sources at a different platform like individual blogs, online feedback, and social network are proliferating and gaining new opportunities and challenges that can be actively exploited using information technology to seek and comprehend people's opinions. In today's field people or entrepreneurs before taking any decision they must be considering the opinion of peoples or information networks. Most of them express the view or opinion through social media platform like Tweeter, Facebook, or blogs on the internet. Therefore, it is essential to analyze to automatically analyze the immense amount of social data available on the internet. Deep learning (DL) has appeared as an influential machine learning (ML) method that studies the properties of different layers or data and provides more advanced predictive results. The study of DL, along with success in many other practical fields, has been widely used in opinion and emotion analysis in recent years. This review explores new challenges in brainstorming and facilitates DL study and the use of semantic analysis. The analysis focuses mainly on methods that try to solve new challenges identified by empathy programs, compared to those already in place. It also conducts extensive research on its current uses in emotion analysis.


Deep learning; Information extraction; Natural language processing; Opinion mining; Semantic analysis

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DOI: http://doi.org/10.11591/ijeecs.v30.i1.pp469-480


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