The usage of social media is increasing by leaps and bounds in our day-to-day lives. It affects daily routines and brings a lot of change in different departments like health and education systems during the COVID-19 pandemic. Healthcare research and practice have been significantly impacted by the astounding growth of social media. Social media are changing health information management in several ways, from offering appropriate ways to enhance healthcare professional contact and share health-related knowledge and experience to facilitating the development of innovative medical research and wisdom. Social media analytics (SMAs) are efficient and effective interaction instruments that can be useful for both patients and clinicians in health interventions. Moreover, a significant portion of those involved in clinical practices (such as clinicians, professional colleges, and departments of health) are unaware of the importance of social media, its potential applications in their daily lives, as well as the possible consequences and how these will be handled. In the presented study, we proposed MCDM-based approaches known as "Criteria Importance Through Inter Correlation" (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in order to identify the effective alternative among several options and make a better decision. After extracting features from the literature review, we choose six significant and relevant features and assign weights to them using CRITIC techniques while utilizing the TOPSIS technique to rank the alternatives based on their performance values. After the implementation of both methods and evaluation procedure, it is determined that the alternative with the highest score is placed at the top and called the "best alternative," while the alternative with the lowest score is placed at the bottom and called the worst alternative. Finally, we suggest a variety of research initiatives and new research areas where the aforementioned procedures become extremely useful in evaluating SMAs and their uses in online health interventions.
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