پارسا عباس زاده

Social networks are expanding nowadays. Social network is a social structure that consists of nodes and these nodes are connected by one or more specific types of dependence. One of the important issues in this field is the detection of influential nodes and its tracking, which has been examined from different perspectives. Among the applications of tracking and identifying influential nodes, we can mention the tracking and monitoring of dangerous criminals, online advertising and marketing.Social networks often change over time, which includes the addition and removal of network nodes and changes in the connections between these nodes, as well as changes in the structure of communities. Each person may have changes over time in terms of role and position, and these changes have been examined with rise-fall and rise-decline. Identifying the role of the node and its connections is important in many applications and social networks. In the researches that have been carried out in this field, the tracking of influential nodes has been investigated from different perspectives, but there is no research that has comprehensively and completely investigated the operation of tracking influential nodes. Therefore, this research has investigated the tracking of influen-tial nodes in such a way that it creates a history of a node in the time periods it has been pre-sent in the network and examines the evolution of these nodes in all the periods it is present in the network. This work is done in such a way that the history of the node's evolution is made in the shortest possible time, and also by using support vector machine learning algo-rithms and random forest, it predicts the impact of a node in the upcoming or future time period based on learning eva‎luation criteria. The current machine has very high accuracy.

شبكه اجتماعي , گره تأثيرگذار , رديابي گره‌هاي تأثيرگذار , جوامع پويا

Social Network , influential nodes , tracking influential nodes , Dynamic networks

parsa abbaszadeh

dr.Hasan Naderi