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The growing adoption of social media services such as YouTube, Facebook, and Twitter have created opportunities for information dissemination practise that has not existed before. This practice improves situational awareness and eases dissemination of information. However, the major challenge is to efficiently extract relevant information from the large volumes of noises. It makes the social data analysis task is extremely labour intensive and time-consuming. To overcome these challenges, we propose a service-based approach to illustrate and analyse social media services. First, we assign social media as a service, called social media service. We also identify its functional and nonfunctional features. Secondly, we plan experiments on realworld datasets for a variety of topics. We analytically evaluate the functional and non-functional features of social media services. The analysis has depicted that classifying functional features and identifying non-functional features such as relatedness, preferences, and engagement of social media services is important regarding analysing social sensors data. This work demonstrates the competence of social media services regarding the Social Media Service-Based Analysis Model. The identified functional and nonfunctional features in this work help data analyst to understand and comprehend the nature of social media services particularly in the subject of Syria war, dengue outbreak and natural disaster. Furthermore, we have provided future research issues from where our work has ended.

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