Analysis of Social Networks using Naive Bayes

被引：0

作者：

Kanakia, Harshil ^{[1
]}

Raundale, Pooja ^{[1
]}

Britto, Ryan ^{[1
]}

Sawardekar, Rohit ^{[1
]}

机构：

[1] Sardar Patel Inst Technol Mumbai, MCA Dept, Mumbai, Maharashtra, India

来源：

PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS) | 2019年

关键词：

Social Networks (SNs); Machine Learning; R-Studio; Naive Bayes; Tableau; CSV;

D O I：

暂无

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 Networking (SN) has become the integral part of our lives, in one form or another; people communicate with each other, through social networking sites. Photos, videos, blogs, messages etc. are the major means of communication. In this paper, the authors have analyzed four different SNs mainly, WhatsApp, LinkedIn, Facebook and Instagram. The trends people follow at each and every stage of human life cycle are also studied and analyzed. The primary data has been collected through interaction with users. It was then cleaned using preprocessor. The machine learning played important role in the analysis. The study inferred some interesting facts about SNs. The paper highlights the analysis of social networks. The critical study is presented in the paper.

引用

页码：88 / 91

页数：4

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