Improving micro-macro businesses on social networks using business intelligence solutions

Throughout history, people in every society have always been thinking of buying and selling goods and creating markets. By the advent of the Internet, the concept of e-commerce has made it possible to design e-business positions around the world. With the boom of social communities, e-business owners have targeted these communities and have always sought to grow their customers among social network users and used these networks to advertise their products and services Increasing data has led to the development of a set of techniques and tools called business intelligence to convert bulk data from different sources into meaningful information to facilitate decision-making in e-commerce. This research introduces a criterion for identifying central nodes of the network to improve micro / macro businesses in social networks The benchmark suggested as a solution to business intelligence, identifies the most important nodes in the social network using the criteria of PageRank, Betweenness centrality, Degree centrality, Closeness centrality, and it recommends to apply these nodes for business intelligence strategies. The intimated solution of this research is evaluated in a data mining process on data located on the Facebook social network. The results show that the proposed hybrid criterion is capable of identifying central nodes in social networks and can be used in line with business intelligence goals and strategies.

کلیدواژه ها:

Social Network ، Business Intelligence ، Hybrid Criteria ، Page Rank ، Betweenness centrality ، Degree centrality ، Closeness centrality