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

IF 2.5 4区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Informatics for Health & Social Care Pub Date : 2021-12-02 Epub Date: 2021-04-20 DOI:10.1080/17538157.2021.1905642
Thilagavathi Ramamoorthy, Dhivya Karmegam, Bagavandas Mappillairaju
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引用次数: 4

Abstract

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.

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基于疾病的社会网络分析和网络建模的社会媒体数据的使用:系统综述。
传染病和非传染性疾病造成的负担正在以惊人的速度增加。社交媒体的使用正在迅速增长,并已成为沟通的新规范。必须检查社交媒体上正在讨论的关于疾病或状况的内容以及参与讨论的人的网络特征。目的是评估使用网络分析和网络建模来研究社交媒体疾病网络的工具和技术。PubMed和IEEEXplore从2009年到2020年进行了检索,筛选和分析后纳入了30项研究。Twitter、QuitNet和特定疾病的在线论坛被广泛用于研究各种健康状况的交流。大多数研究都进行了内容分析和网络分析,只有6项研究进行了网络建模。关于癌症、COVID-19和吸烟的帖子已经被广泛研究。列出了用于网络分析的工具和技术。与健康相关的社交媒体数据可以用于网络分析。网络建模技术将有助于识别与疾病网络隶属关系相关的结构因素,这一点很少得到利用。这将有助于公共卫生专业人员制定有针对性的干预措施。
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来源期刊
CiteScore
6.10
自引率
4.20%
发文量
21
审稿时长
>12 weeks
期刊介绍: Informatics for Health & Social Care promotes evidence-based informatics as applied to the domain of health and social care. It showcases informatics research and practice within the many and diverse contexts of care; it takes personal information, both its direct and indirect use, as its central focus. The scope of the Journal is broad, encompassing both the properties of care information and the life-cycle of associated information systems. Consideration of the properties of care information will necessarily include the data itself, its representation, structure, and associated processes, as well as the context of its use, highlighting the related communication, computational, cognitive, social and ethical aspects. Consideration of the life-cycle of care information systems includes full range from requirements, specifications, theoretical models and conceptual design through to sustainable implementations, and the valuation of impacts. Empirical evidence experiences related to implementation are particularly welcome. Informatics in Health & Social Care seeks to consolidate and add to the core knowledge within the disciplines of Health and Social Care Informatics. The Journal therefore welcomes scientific papers, case studies and literature reviews. Examples of novel approaches are particularly welcome. Articles might, for example, show how care data is collected and transformed into useful and usable information, how informatics research is translated into practice, how specific results can be generalised, or perhaps provide case studies that facilitate learning from experience.
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