Paper Info
Title
A Proposal for Book Oriented Aspect Based Sentiment Analysis: Comparison over Domains.
Abstract
Aspect-based sentiment analysis (absa) deals with extracting opinions at a fine-grained level from texts, providing a very useful information for companies which want to know what people think about them or their products. Most of the systems developed in this field are based on supervised machine learning techniques and need a high amount of annotated data, nevertheless not many resources can be found due to their high cost of preparation. In this paper we present an analysis of a recently published dataset, covering different subtasks, which are aspect extraction, category detection, and sentiment analysis. It contains book reviews published in Amazon, which is a new domain of application in absa literature. The annotation process and its characteristics are described, as well as a comparison with other datasets. This paper focuses on this comparison, addressing the different subtasks and analyzing their performance and properties.
Year
DOI
Venue
2018
10.1007/978-3-319-91947-8_1
Lecture Notes in Computer Science
Keywords
Field
DocType
Aspect-based sentiment analysis,Book reviews Datasets,Annotation,Evaluation
Annotation,Computer science,Sentiment analysis,Natural language processing,Artificial intelligence
Conference
Volume
ISSN
Citations 
10859
0302-9743
0
PageRank 
References 
Authors
0.34
12
4
Name
Order
Citations
PageRank
tamara alvarezlopez1534.09
Milagros Fernández Gavilanes2516.01
Enrique Costa-Montenegro334326.83
Patrice Bellot424151.18