Identification and Assessment of Adverse Events Using Smart Social Media Platforms

Abstract

In recent years, social media becomes a new source where information has grown in an immense proportion as well as continues to develop. In terms of global users, social networks have perceived an exceptional development (such as Twitter has over 645,750,000 handlers on 11th July 2014 and develops by a projected rate of 135,000 handlers each day, producing 9100 tweets per second). In social media, huge population of patients are actively engaged in posting/sharing health connected social media data as well as specifically health social networks. Recently, Pew Research Center's conducted a survey that has revealed the social media significance according to current scenario public health, describing that 34% of healthcare workers as well as 20% of patients observe or read other's online experience/opinion. Furthermore, 6% of patients as well as 11% of caregivers post questions and share experiences online. Health related social networks have been attracting several users particularly focusing on health-related problems. In these social media platforms (such as e.g., Daily Motion, Vkontakate), handlers converse their experiences about health-related issues involving the prescribed drugs usage, treatments and side effects. Users consistently share their experiences with others who are facing same issues and consequences that makes these social networks exceptional as well as robust sources of data on treatments, drugs and health. Because of the emergence of these social media as well as the plentiful of information from them, exploration on ADR monitoring or public health monitoring, has concentrated on manipulating info from such sources recently. Monitoring public health involves research on smoking cessation configurations on Facebook, monitoring malpractice and detecting the user social circles with general clinical experiences such as drug abuse. When several patients suffering from the similar disease or use certain prescription, share data about their drug results, treatments or symptoms, this data can deliver valuable medical insights for both health-related trades and patients that go beyond conventional communication approaches.