Visualization Of Character Relationships Based On Event Association

With the rapid development of social networks,the number of social media networks is rapidly increasing,the relationship is complex,and the relationship between the associated events also shows a complex and corresponding changes,so it is very meaningful to visualize the network of relationship based on associated events.On the basis of the existing research work,aiming at the characteristics of the character relations network,this paper study the layout algorithm,the social division and the visual design of the ego network based on the event related character network respectively.The research contents of this paper include:Firstly,research on the algorithm of character relationship network layout based on the event is considered.Aiming at the characteristic that the network of characters changes with the changing of related events,the attribute of events and the importance of nodes are considered synthetically to improve the force-directed algorithm of a network of relationship based on events.The results show that there is a high concentration of people associated with the event,and that important characters are located in the center of the canvas,reducing the visual confusion and more in line with the aesthetic standards.It can help users quickly explore the potential relationships between people,important people,and the potential relationships between people and events.Secondly,association of social networks based on event correlation module degree is carried out.Everyone has its own unique social circle,so the network of character relationships often shows the phenomenon of associations.The traditional grouping of affiliate networks usually only divides the group of affiliates for the same event and can not deal with the grouping of affiliates based on the affiliation of affiliates.In this paper,we propose a method of dividing the relationship between people and organizations based on the relevance of the event-related modules.Based on the characteristics of the relationship of the events,we extend the concept of modularity to get the module-based degree.Then,we get the associated people relationship network for community segmentation.Finally,using the Star Wars dataset to compare the proposed method and the traditional modular algorithm,the validity of the method is verified.Finally,network analysis of personal characters based on event association is proposed.Aiming at the characteristics of time-series events in ego network,this paper helps users to quickly explore the personal relationship network with the changes of events through the comprehensive utilization of personal network evolution map,tag cloud,personal trends and personal network diagram of all events changing trends and the relationship between individual neighbor nodes and other information.