Presentation of a new algorithm to predict the position of users in social networks using centrality criteria and neural network

The IJNCPS's Authors that presented the article:

  • mohammadreza Mohmmadrezaei 1Department of Computer, Ramhormoz Branch, Islamic Azad University, Ramhormoz, Iran


Social networking sites are Web sites where users can subscribe to and share their information. Social networks are divided into two categories of online social networks and offline social networks. To research in the field of social networking, we need to model social networks. There are several ways to model social networks, we want to graph with the social network model in which the nodes represent the users and the edges represent the connection between the users. The measures for evaluating and determining the position of users in social networks are centrality measures. there are so many social networks available. Now, we are looking at where each user is position on social networks. In fact, we want to calculate and predict the position of users on social networks in specific time periods, when the network was 100 million members, what would be the position of 1 million users who joined the network early on, the good news is that we do not need to continuously calculate the cost of computing centrality indicators.