Technological advancements and their adaptation have made social media one of the most used platforms for sharing ideas and expressing views and experiences. Fields like finance and retail have mined and used information on social platforms to a good effect. The healthcare domain too can leverage social forums in various ways, and it has just started its journey by taking baby steps. Events like the COVID-19 pandemic have accelerated the adaptation to increase the pace and breadth of information outreach. The chapter discusses social media usage in healthcare. The chapter highlights challenges, opportunities, and issues encountered so far and the way forward.
TopIntroduction
Social media adaptation has grown leaps and bounds in the last few years. Its usage for healthcare is comparatively slow when compared with fields like finance, sports, or even its adoption for generic sharing of thoughts and opinions. The reason for slow adoption in the field of health can be attributed to privacy and an inherent reluctance to share one's experiences which are very personal to individuals.
Different entities that can be involved in exchanges related to healthcare can be - Individual to Individual, Individual to Expert, Individual to Public. All three communication channels are possible with different degrees of involvement. Individual to public exchanges can happen in generic social platforms like Twitter, Facebook, or any similar platform. While others have a pretty limited scope and are more proctored.
The growth of acceptance of social media as a platform to share views, experiences, and feelings is enabling its outreach to the healthcare domain. Currently, there is a lot of information getting poured (Figure 1) in, and unless it gets processed to extract insights it will be just like a pile of raw data hardly providing any value. This is where the contribution from new technology is leveraged. Technologies like Artificial Intelligence (AI), Machine Learning (ML), Data Mining (DM), Data Science (DS), and Analytics are utilized to get value from the data.
Like all the domains that attempt at applying Natural Language Processing (NLP) to decipher the text written to express one's views, the healthcare field too comes with its own challenges. (Padmavathy & Pakkir Mohideen, 2020) have studied the best Sentiment Analysis (SA) technique to examine people's opinions by analyzing the language used on different medical forums. Their findings were not that unique and clearly signified that like all other fields, application of NLP is not going to be straightforward, they expressed it verbatim ‘Despite the fact that most reviews of doctors/ medical practitioners and medicines/drugs are written by non-professional users, reviews of physicians are distinguished by the use of informal language, while reviews of drugs are characterized by a mixture of informal language and technical medical terms with greater lexical diversity, making SA difficult’. Thus again signifying the potential and challenges that exist together.
Figure 1. Various social media data sources used by NLP for sentiment analysis
Chapter first reviews the existing usage of social media in the field of healthcare and how modern-day technology innovations are finding new ways to pace up the cycle of inception to delivery in various fields. It discusses the potential aspects that can be extended in each field. We conclude with innovative usage of this immensely powerful technological concept in one of the most important domains for humans.
TopBackground
The field of healthcare can have multiple subfields – medical, pharmaceutical, psychological, epidemical, and many more. In essence, all these domains are interrelated and are concerned with human well-being. Few of these subfields have leveraged the power of social media, while few are laggards. This section provides a comprehensive review of the adoption of social media in various subfields of healthcare.