A Comprehensive Survey on Aspect Based Sentiment Analysis
A Comprehensive Survey on Aspect Based Sentiment Analysis
Aspect Based Sentiment Analysis (ABSA) is the sub-field of Natural Language Processing that deals with essentially splitting our data into aspects ad finally extracting the sentiment information. ABSA is known to provide more information about the context than general sentiment analysis. In this study, our aim is to explore the various methodologies practiced while performing ABSA, and providing a comparative study. This survey paper discusses various solutions in-depth and gives a comparison between them. And is conveniently divided into sections to get a holistic view on the process.
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Computation and Language, Computation and Language (cs.CL), Machine Learning (cs.LG)
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Computation and Language, Computation and Language (cs.CL), Machine Learning (cs.LG)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
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