In the realm of interconnected digital world, social ranking systems are readily used in different sections of society, for several reasons. The private and public sectors both are making use of social ranking systems as a tool to engineer human behavior, and crafting a digitally stimulated social control. Online reviews and ratings are one of the significant marketing strategies of online sellers to steer out consumers' opinion and ultimately their purchasing decisions. Buyers usually go through these reviews and ratings while purchasing online product or hiring online services. Online consumer reviews, recommendations for product and services, and peer viewpoints play a significant role in the customer's opinion formation. Different online forums of product reviews, ratings and recommendations differ in their objectives, functions, and characteristics. This paper focuses upon a systematic literature review and comparative study of the influence the positive and negative reviews and ratings of the products, automobile services, movies, restaurants, products and services on OLX & eBay, etc. have on opinion formation. Moreover, how these reviews influence others opinions of buying and using the products, services and apps will be analyzed.

Cloud computing with an amalgamation of the internet of things (IoT) typically gave birth to an ideal field called Cloud of things (CoT). CoT maintains revolutionary services in every domain, but it has instantly become a rising star in smart transportation because a well-organized facility might present a challenge for dealing with the exponentially expanding people living in smart cities. Lack of management in transport can cause distress among people and nowadays parking has come to be one of the critical issues faced by the public daily. In this paper, we present a parking availability prediction model implemented within a geo-fence ranging from 100-150 meters based on cloud, IoT, and GIS. In contrast to present models, instead of offering no space or parking is full; our model accurately determines the ETA of a vehicle and checks the potential/chance of parking availability. It also calculates the time for the next parking space if the existing parking space accessibility is zero. Moreover, our model includes all the exogenous factors like weather, time zone conditions to gain prediction accuracy.