Research Article
Document Level Sentiment Analysis: A survey
@ARTICLE{10.4108/eai.14-3-2018.154339, author={S. Behdenna and F. Barigou and G. Belalem}, title={Document Level Sentiment Analysis: A survey}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={4}, number={13}, publisher={EAI}, journal_a={CASA}, year={2018}, month={3}, keywords={opinion mining, sentiment analysis, opinion, review, document, machine learning.}, doi={10.4108/eai.14-3-2018.154339} }- S. Behdenna
F. Barigou
G. Belalem
Year: 2018
Document Level Sentiment Analysis: A survey
CASA
EAI
DOI: 10.4108/eai.14-3-2018.154339
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.
Copyright © 2018 S. Behdenna et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
