Semantic Scholar Open Access 2021 219 sitasi

Machine learning algorithms for social media analysis: A survey

Balaji T.K. Chandra Sekhara Rao Annavarapu Annushree Bablani

Abstrak

Abstract 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.

Topik & Kata Kunci

Penulis (3)

B

Balaji T.K.

C

Chandra Sekhara Rao Annavarapu

A

Annushree Bablani

Format Sitasi

T.K., B., Annavarapu, C.S.R., Bablani, A. (2021). Machine learning algorithms for social media analysis: A survey. https://doi.org/10.1016/J.COSREV.2021.100395

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Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
219×
Sumber Database
Semantic Scholar
DOI
10.1016/J.COSREV.2021.100395
Akses
Open Access ✓