Abstract
Tremendous amount of topics and opinions are available on the internet these days through using social media. All evidences proof that these opinions play important role in our life and affect on behaviors of communities and governments. Availability of this effective data on social media opens the door to scholars to develop automatic systems for detecting these opinions. Many online tools are available nowadays for opinion mining of micro-blogs with different languages. Most of these tools detect the corresponding opinion to a given micro-blog independently and some of them find opinion towards a specific target (entity) in the micro-blog. In this paper, we introduce a comprehensive review on sentiment analysis in social media. A survey on target dependent sentiment analysis is presented also with summarized results. Our study finds some gaps that can be filled in future research and illustrates that there are still many limits in previous research works. Some discussions are included in this survey on target dependent sentiment analysis as promising future research direction.
| Original language | English |
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| Title of host publication | 2017 9th IEEE-GCC Conference and Exhibition, GCCCE 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Print) | 9781538627563 |
| DOIs | |
| State | Published - 27 Aug 2018 |
Publication series
| Name | 2017 9th IEEE-GCC Conference and Exhibition, GCCCE 2017 |
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Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- Machine Learning
- Opinion Mining
- Sentiment Analysis
- Social Media
- Target Dependent
- Text Analysis
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
- Information Systems and Management
- Media Technology
- Instrumentation