Data Analytics of Social Networking sites using Game Theory Model

Abstract

Decision making tools provides substantial supports to companies as to optimize their strategies with respect to their competitors. The end users or say the consumers’ satisfaction plays the key role in the Decision making. The application under this research work is based on two giants of the social networking sites viz Facebook and Instagram. The primary requirement of a Game theory model is to have such competitors or says players and their interaction parameters. The first step is to identify the common features between these two players which satisfy the interaction criterion. These are the called interactive strategies under consideration. A heterogeneous group of frequent users of these two social networking sites is selected using simple random sampling. The reliability of the questionnaire, formed on the basis of interactive parameters, is tested by using Cronbach's alpha test. The graphical and descriptive statistics give the initial trends of the end users. The regression analysis is carried out where the intercept data is collected as payoff values. This leads to the formation of the two player Game theory model. As the final result, the optimum strategies of each player and the value of the game are calculated. The interpretation of the calculated values reflects the influence of decision making for the optimum strategies under the game theory model.