Use of social media data for disease based social network analysis and network modeling: A Systematic Review

被引:5
|
作者
Ramamoorthy, Thilagavathi [1 ]
Karmegam, Dhivya [1 ]
Mappillairaju, Bagavandas [2 ]
机构
[1] SRM Inst Sci & Technol, Sch Publ Hlth, Kattankulathur 603203, Tamil Nadu, India
[2] SRM Inst Sci & Technol, Ctr Stat, Kattankulathur 603203, Tamil Nadu, India
关键词
Social network analysis; infectious diseases; non-communicable diseases; social media; network modeling; COVID-19;
D O I
10.1080/17538157.2021.1905642
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Burden due to infectious and noncommunicable disease is increasing at an alarming rate. Social media usage is growing rapidly and has become the new norm of communication. It is imperative to examine what is being discussed in the social media about diseases or conditions and the characteristics of the network of people involved in discussion. The objective is to assess the tools and techniques used to study social media disease networks using network analysis and network modeling. PubMed and IEEEXplore were searched from 2009 to 2020 and included 30 studies after screening and analysis. Twitter, QuitNet, and disease-specific online forums were widely used to study communications on various health conditions. Most of the studies have performed content analysis and network analysis, whereas network modeling has been done in six studies. Posts on cancer, COVID-19, and smoking have been widely studied. Tools and techniques used for network analysis are listed. Health-related social media data can be leveraged for network analysis. Network modeling technique would help to identify the structural factors associated with the affiliation of the disease networks, which is scarcely utilized. This will help public health professionals to tailor targeted interventions.
引用
收藏
页码:443 / 454
页数:12
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