A Systematic Review on Implicit and Explicit Aspect Extraction in Sentiment Analysis

Jaafar Zubairu Maitama,Rosmadi Fauzi,Norisma Idris,Liyana Shuib,Asad Abdi

doi:10.1109/access.2020.3031217

Jaafar Zubairu Maitama, Rosmadi Fauzi + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.3031217

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Abstract

Aspect-based sentiment analysis (ABSA) is currently among the most vigorous areas in natural language processing (NLP). Individuals, private and government institutions are increasingly using media sources for decision making. In the last decade, aspect extraction has been the most essential phase of sentiment analysis (SA) to conduct an abridged sentiment classification. However, previous studies on sentiment analysis mostly focused on explicit aspects extraction with limited work on implicit aspects. To the best of our knowledge, this is the first systematic review that covers implicit, explicit, and the combination of both implicit and explicit aspect extractions. Therefore, this systematic review has been conducted to, 1) identify techniques used for extracting implicit, explicit, or both implicit and explicit aspects; 2) analyze the various evaluation metrics, data domains, and languages involved in the implicit and explicit aspect extraction in sentiment analysis from years 2008 to 2019; 3) identify the key challenges associated with the techniques based on the result of a comprehensive comparative analysis; and finally, 4) highlight the feasible opportunities for future research directions. This review can be used to assist novice and prominent researchers to understand the concept of both implicit and explicit aspect extractions in aspect-based sentiment analysis domain.

Highlights

The explosive magnification of social media on the Internet has helped people to receive information on the networks and in the generation of information to others
The result showed that precision, recall, F-measure as well as accuracy are the 4 major evaluation metrics used in the aspect extraction
Our analysis showed that combination of precision, recall together with f-measure on the same study as metric for implicit, explicit or the combined implicit and explicit aspect extraction helps in achieving optimal performance of the models

Summary

Introduction

The explosive magnification of social media on the Internet has helped people to receive information on the networks and in the generation of information to others. Online interaction is becoming more real, in which people can discuss and give information about individual or topic on social networks such as Twitter, forums, Facebook, Instagram, etc. There is a special kind of information which is opinions, evaluations, feelings, and attitudes [1]. This information comes implicitly from the users or customers when they discuss the services or products they have used, or about the social events they have witnessed in their lives. Online interaction changes the traditional purchasing behaviors, as well as social studies.

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