Machine learning algorithms for social media analysis: A survey

被引:92
|
作者
Balaji, T. K. [1 ]
Annavarapu, Chandra Sekhara Rao [2 ]
Bablani, Annushree [1 ]
机构
[1] Indian Inst Informat Technol, Dept Comp Sci & Engn, Sri City 517646, Andhra Pradesh, India
[2] Indian Sch Mines, Indian Inst Technol, Dept Comp Sci & Engn, Dhanbad 826004, Jharkhand, India
关键词
Social Media; Machine learning; Social network analysis; Applications of social media analysis; SENTIMENT ANALYSIS; RECOMMENDER SYSTEMS; BIG DATA; BEHAVIORAL-ANALYSIS; DESTINATION IMAGE; FEATURE-SELECTION; NEURAL-NETWORKS; CLASSIFICATION; TWITTER; USER;
D O I
10.1016/j.cosrev.2021.100395
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Social Media (SM) are the most widespread and rapid data generation applications on the Internet increase the study of these data. However, the efficient processing of such massive data is challenging, so we require a system that learns from these data, like machine learning. Machine learning methods make the systems to learn itself. Many papers are published on SM using machine learning approaches over the past few decades. In this paper, we provide a comprehensive survey of multiple applications of SM analysis using robust machine learning algorithms. Initially, we discuss a summary of machine learning algorithms, which are used in SM analysis. After that, we provide a detailed survey of machine learning approaches to SM analysis. Furthermore, we summarize the challenges and benefits of Machine Learning usages in SM analysis. Finally, we presented open issues and consequences in SM analysis for further research. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页数:32
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