Közösségi média kommunikáció a digitális egészségügyi térben
Social media communication in the digital medical space
Comparative analysis of #cysticfibrosis and #Asthma Big Data
Author(s): Sára SimonSubject(s): Social Sciences
Published by: Debreceni Egyetem Politikatudományi és Szociológiai Intézet
Keywords: digital healthcare; e-patients; Big Data; cystic fibrosis; asthma
Summary/Abstract: In the environment of 21st century technology, the transformation of information acquisition of health care and patients has had an increasing emphasis. Despite the earlier authoritative doctor-patient relationship, a need for an equal, cooperation-based communication has emerged and there are so many digital healthcare projects to achieve this (Koskova 2015). Information acquisition on the internet has allowed patients that based on the increasingly available medical information they acquire information about their condition, become part of patient communities, ask for second opinions, and become committed helpers of their doctors in their disease (Meskó et. al 2017).This can be especially true for patients with rare diseases, where a diagnosis might take even a decade, the patient needs lifelong condition maintenance and treatment, if it is available. While the proportion of patients with rare diseases is low compared to the whole of society, the number of such patients is approximately 30 million in Europe (EURORDIS), which means patients and their relatives need not only a harmonized health care system, but extensive information so that they can live with the rare disease with less difficulty. The aim of our study was to present the options of information acquisition in the social media, focusing on Twitter, via an interdisciplinary and social approach. In this study therefore we carried out a Big Data based social media analysis based on #Asthma and #CysticFibrosis databases of the Symplur corporation. This study results contain the complete online communication of 7 years (2012-2019) regarding these hashtags. The analysis has few levels including semantic research, stakeholder and hashtag review, engagement, and the whole tweet activity exploration.
Journal: Metszetek - Társadalomtudományi folyóirat
- Issue Year: 10/2021
- Issue No: 3
- Page Range: 143-180
- Page Count: 38
- Language: Hungarian