Survey on Target Dependent Sentiment Analysis of Micro-Blogs in Social Media

被引:0
作者
Abudalfa, Shadi [1 ]
Ahmed, Moataz [1 ]
机构
[1] King Fahd Univ Petr & Minerals, ICS Dept, Dhahran, Saudi Arabia
来源
2017 9TH IEEE-GCC CONFERENCE AND EXHIBITION (GCCCE) | 2018年
关键词
Opinion Mining; Text Analysis; Sentiment Analysis; Target Dependent; Machine Learning; Social Media; OPINION;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:155 / 160
页数:6
相关论文
共 83 条
[1]   Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums [J].
Abbasi, Ahmed ;
Chen, Hsinchun ;
Salem, Arab .
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2008, 26 (03)
[2]   SAMAR: Subjectivity and sentiment analysis for Arabic social media [J].
Abdul-Mageed, Muhammad ;
Diab, Mona ;
Kuebler, Sandra .
COMPUTER SPEECH AND LANGUAGE, 2014, 28 (01) :20-37
[3]  
Abdulla N., 2013, 2013 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), P1, DOI [10.1109/AEECT.2013.6716448, DOI 10.1109/AEECT.2013.6716448]
[4]  
Ahmed S. I., 2014, THESIS
[5]  
Ahmed S, 2013, IEEE INT CONF INNOV
[6]  
Al-Kabi MN, 2014, INT J ADV COMPUT SC, V5, P181
[7]  
Alhumoud S.O., 2015, International Journal of Social, Behavioral, Educational, Economic and Management Engineering, V9
[8]  
[Anonymous], THESIS
[9]  
[Anonymous], 2015, J. Big Data, DOI [DOI 10.1186/S40537-015-0015-2, 10.1186/s40537-015-0015-2]
[10]  
[Anonymous], 2010, Proceedings of the 23rdInternational Conference on Computational Linguistics: Posters