Challenges and Recommended Solutions in Multi-Source and Multi-Domain Sentiment Analysis
Document Type
Article
Publication Date
1-1-2019
Abstract
The massive availability of online reviews and postings in social media offers invaluable feedback for businesses to make better informed decisions in steering their marketing strategies towards users' interests and preferences. Sentiment analysis is, therefore, essential for determining the public's opinion towards a particular topic, product or service. Traditionally, sentiment analysis is performed on a single data source, for instance, online product reviews or Tweets. However, the need to develop a more precise, and more comprehensive result has steered the move towards performing sentiment analysis on multiple data sources. The use of multiple data sources for a particular domain of interest can increase the amount of datasets needed for training a sentiment classifier. Till now, the problem of insufficient datasets for training the classifier is only addressed by multi-domain sentiment analysis. Aiming to equip researchers with a thorough understanding on both multi-source and multi-domain sentiment analysis, this paper aims to identify the underlying challenges of multi-source and multi-domain sentiment analysis, and discuss the solutions applied by the researchers concerned. This paper also offers an insightful discussion of the findings derived from past studies, and based on these, propose some useful suggestions for the future direction of this research area. Findings derived from our review would be beneficial towards guiding researchers towards the future progress and advancement of multi-source and multi-domain sentiment analysis. © 2013 IEEE.
Keywords
multi-domain, multi-source, natural language processing, Sentiment analysis, transfer learning
Divisions
deputyresearch
Funders
Ministry of Education, Malaysia, through the Malaysian Higher Education Consortium of Halal Institute Grant, and in part by the University of Malaya for Providing the Facilities and Infrastructure to Conduct the Research under Grant MO001-2018
Publication Title
IEEE Access
Volume
7
Publisher
Institute of Electrical and Electronics Engineers